scholarly journals The unique experience of the accumulation of Ukrainian national capital in conditions of the interwar Poland

2018 ◽  
Vol 2018 (51) ◽  
pp. 176-195
Author(s):  
Oksana Verbova ◽  
Keyword(s):  
Interwar Poland ◽  
National Capital ◽  
Unique Experience

Unique Experience of Women Soldiers During and After Deployment

2013 ◽  
Author(s):  
Johanna E. Nilsson ◽  
Laverne A. Berkel ◽  
Patricia Kelly ◽  
Joanna Maung ◽  
Dagoberto Heredia ◽  
...  
Keyword(s):  
Women Soldiers ◽  
Unique Experience

Russia in international capital movement: Turn of tendencies

2017 ◽  
pp. 148-158 ◽  
Author(s):  
A. Bulatov
Keyword(s):  
Industrial Structure ◽  
Prima Facie ◽  
Capital Movement ◽  
International Capital ◽  
Capital Outflow ◽  
The Past ◽  
Russian Economy ◽  
National Capital ◽  
Future Situation ◽  
International Capital Movement

The paper deals with the past, current and future situation in Russian capital outflow and inflow. The specific features of the past situation (2001-2013) were as follows: big scale of Russian participation in international capital movement; turnover of national capital between Russia and offshores; stable surplus of capital outflow over inflow; inadequacy of industrial structure of capital inflow to Russian needs. The current situation is characterized by such new features as radical cut in volumes of capital outflow and inflow, some decrease in its level of offshorization. In the mid-term the probability of continuation of current trends is high. In the long-term the mode of Russian participation in international capital movement will prima facie depend on prospects of realization of systematic reforms in the Russian economy.

Does Brand Awareness Impact Purchase Decision: A Case of Organic Grocery

2018 ◽  
Vol 6 (7) ◽  
pp. 45
Author(s):  
Gunjan Gumber ◽  
Jyoti Rana
Keyword(s):  
Organic Food ◽  
Brand Awareness ◽  
National Capital Region ◽  
Promising Alternative ◽  
Brand Recall ◽  
Brand Building ◽  
Brand Recognition ◽  
National Capital ◽  
High Level ◽  
Structured Questionnaire

In India, the concept of organic food is gaining widespread acceptability. Consumers are becoming more conscious about their health and are looking for food that serves as a promising alternative. Corporates, NGOs, Spiritual leaders and Government are also promoting this food, as it is free from irradiation, chemicals and artificial additives. A number of organic food brands are available in the market. The main objective of this study is to find out the level of brand awareness and its influence on purchase of organic grocery. The data was collected from 150 organic consumers in National Capital Region (Delhi, Gurgaon, Faridabad and Noida) through a structured questionnaire. Questions related to brand recall, brand recognition and purchase of organic grocery were asked. It was found that in general, there is a low level of brand awareness among consumers, and those who have high level of awareness; they consume organic grocery more often. The study will help corporates to make effective communication and brand-building strategies.

The beginning of phygital world

2020 ◽  
Vol 10 (2) ◽  
pp. 1-4
Author(s):  
Evgeny Soloviov ◽  
Alexander Danilov
Keyword(s):  
Big Data ◽  
Learning Styles ◽  
21St Century ◽  
Digital Technology ◽  
Aviation Education ◽  
Digital World ◽  
The World ◽  
Unique Experience ◽  
Smart Data

The Phygital word itself is the combination pf physical and digital technology application.This paper will highlight the detail of phygital world and its importance, also we will discuss why its matter in the world of technology along with advantages and disadvantages.It is the concept and technology is the bridge between physical and digital world which bring unique experience to the users by providing purpose of phygital world. It is the technology used in 21st century to bring smart data as opposed to big data and mix into the broader address of array of learning styles. It can bring new experience to every sector almost like, retail, medical, aviation, education etc. to maintain some reality in today’s world which is developing technology day to day. It is a general reboot which can keep economy moving and guarantee the wellbeing of future in terms of both online and offline.

Analysis of Sentiment of Moving a National Capital with Feature Selection Naive Bayes Algorithm and Support Vector Machine

2020 ◽  
Vol 4 (3) ◽  
pp. 504-512
Author(s):  
Faried Zamachsari ◽  
Gabriel Vangeran Saragih ◽  
Susafa'ati ◽  
Windu Gata
Keyword(s):  
Social Media ◽  
Support Vector Machine ◽  
Feature Selection ◽  
Public Opinion ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Capital City ◽  
Support Vector ◽  
National Capital ◽  
Bayes Algorithm

The decision to move Indonesia's capital city to East Kalimantan received mixed responses on social media. When the poverty rate is still high and the country's finances are difficult to be a factor in disapproval of the relocation of the national capital. Twitter as one of the popular social media, is used by the public to express these opinions. How is the tendency of community responses related to the move of the National Capital and how to do public opinion sentiment analysis related to the move of the National Capital with Feature Selection Naive Bayes Algorithm and Support Vector Machine to get the highest accuracy value is the goal in this study. Sentiment analysis data will take from public opinion using Indonesian from Twitter social media tweets in a crawling manner. Search words used are #IbuKotaBaru and #PindahIbuKota. The stages of the research consisted of collecting data through social media Twitter, polarity, preprocessing consisting of the process of transform case, cleansing, tokenizing, filtering and stemming. The use of feature selection to increase the accuracy value will then enter the ratio that has been determined to be used by data testing and training. The next step is the comparison between the Support Vector Machine and Naive Bayes methods to determine which method is more accurate. In the data period above it was found 24.26% positive sentiment 75.74% negative sentiment related to the move of a new capital city. Accuracy results using Rapid Miner software, the best accuracy value of Naive Bayes with Feature Selection is at a ratio of 9:1 with an accuracy of 88.24% while the best accuracy results Support Vector Machine with Feature Selection is at a ratio of 5:5 with an accuracy of 78.77%.

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