Assessing Japan’s Arctic Engagement during the ArCS Project (2015–2020)

As Japan is considered a non-regional actor in Arctic governance, this paper begins with analysing how Japan navigates the web of Arctic governance and how it manages to create a coherent Arctic narrative and engages with the Arctic both inside and outside the region. The present research argues that the construction of an Arctic identity is a praxis performed through time that needs to be constantly reaffirmed. To illustrate this point, the paper then uses a lateral rather than linear approach to assess the influence of the Arctic on Japan at present. This paper assesses Japan’s engagement on the main stage where Arctic governance is performed (i.e. The Arctic Council) since the release of Japan’s Arctic Policy and under the Arctic Challenge for Sustainability project, Japan’s flagship program for Arctic research. Looking to the future, countries such as Japan who are willing to be involved in all parts of Arctic governance will have to make a choice about what kind of Arctic relationships they want to create and in which of these relationships Japan could invest more.

PROBABILISTIC SAFETY OF ESTUARY VESSELS BASED ON NONLINEAR ROLLING IN WIND AND WAVES

In the first place the discusser would like to congratulate Dr. Bačkalov with his paper, in which he assesses the new Belgian safety regulations for estuary vessels by means of a non-linear approach taking account the effect of a combination of beam waves and unsteady beam wind. The results presented are based on a solid, scientific background, and the author’s approach as published in former papers can be considered as the base of a promising methodology for evaluating the stability and safety of a vessel in waves and wind. As the discusser has supported the Belgian federal authorities in defining the methodology and formulating the present regulations, it is a pleasure to learn that the implementation of the latter is considered as a significant step in the general improvement of ship safety regulations.

Customer Co-creation: An Insight on its Influence on Customer Loyalty in the Cosmetic Industry

This article deals with the impact on customer loyalty through the implementation of customer co-creation campaigns in the beauty industry, also referred to as the cosmetic industry; while additionally featuring central points that add to the ability and willingness of a customer to partake in these co-creation campaigns. Co-creation refers to the practice deviced by organizations to team up with their stakeholders during the planning, advancing, and implementing stages of their products and services. “It replaces the hierarchical approach to management and the linear approach to innovation, affording all stakeholders the possibility to influence and bring forth meaningful and relevant solutions in a collaborative environment” (Kirah, A 2009). An exploratory survey was conducted to collect data from 229 respondents, through questionnaires. All the respondents were users of cosmetic products, irrespective of gender; living in the cities of Bangalore and Mysore. Mean, Standard Deviation, Correlation and Factor Analysis were used to analyse the acquired data, and study the outcomes. The findings of the study suggest that the customer co-creation campaigns have a favorable impact on customer loyalty, ultimately resulting in higher customer retention rates. The study also confirms various factors contributing to a customer’s participation in the co-creation campaign.

Tachyonic preheating in plateau inflation

Plateau inflation is an experimentally consistent framework in which the scale of inflation can be kept relatively low. Close to the edge of the plateau, scalar perturbations are subject to a strong tachyonic instability. Tachyonic preheating is realized when, after inflation, the oscillating inflaton repeatedly re-enters the plateau. We develop the analytic theory of this process and expand the linear approach by including backreaction between the coherent background and growing perturbations. For a family of plateau models, the analytic predictions are confronted with numerical estimates. Our analysis shows that the inflaton fragments in a fraction of an e-fold in all examples supporting tachyonic preheating, generalizing the results of previous similar studies. In these scenarios, the scalar-to-tensor ratio is tiny, r < 10-7.

Data Mining in Automotive Warranty Analysis

<p>This thesis is about data mining in automotive warranty analysis, with an emphasis on modeling the mean cumulative warranty cost or number of claims (per vehicle). In our study, we deal with a type of truncation that is typical for automotive warranty data, where the warranty coverage and the resulting warranty data are limited by age and mileage. Age, as a function of time, is known for all sold vehicles at all time. However, mileage is only observed for a vehicle with at least one claim and only at the time of the claim. To deal with this problem of incomplete mileage information, we consider a linear approach and a piece-wise linear approach within a nonparametric framework. We explore the univariate case, as well as the bivariate case. For the univariate case, we evaluate the mean cumulative warranty cost and its standard error as a function of age, a function of mileage, and a function of actual (calendar) time. For the bivariate case, we evaluate the mean cumulative warranty cost as a function of age and mileage. The effect of reporting delay of claim and several methods for making prediction are also considered. Throughout this thesis, we illustrate the ideas using examples based on real data.</p>

Data Mining in Automotive Warranty Analysis

<p>This thesis is about data mining in automotive warranty analysis, with an emphasis on modeling the mean cumulative warranty cost or number of claims (per vehicle). In our study, we deal with a type of truncation that is typical for automotive warranty data, where the warranty coverage and the resulting warranty data are limited by age and mileage. Age, as a function of time, is known for all sold vehicles at all time. However, mileage is only observed for a vehicle with at least one claim and only at the time of the claim. To deal with this problem of incomplete mileage information, we consider a linear approach and a piece-wise linear approach within a nonparametric framework. We explore the univariate case, as well as the bivariate case. For the univariate case, we evaluate the mean cumulative warranty cost and its standard error as a function of age, a function of mileage, and a function of actual (calendar) time. For the bivariate case, we evaluate the mean cumulative warranty cost as a function of age and mileage. The effect of reporting delay of claim and several methods for making prediction are also considered. Throughout this thesis, we illustrate the ideas using examples based on real data.</p>

An Approach for Movie Review Classification in Turkish

Web 2.0 has given to all people the right to become a representative of a huge cast of informal media. The importance of this power is getting more evident everyday. Every social media actor can influence the rest of the world by one’s own opinions, feelings, and thoughts generously shared on multiple media. This information belonging to various fields of life can be very handy and be used to one’s advantage, gaining precious experience. One of the greatest problems that this poses is the huge number of data spread everywhere, which are difficult to process as row data per se. Social media and general sentiment text analysis is of much valuable use, accomplishing the task extracting pure gold out of raw mineral. The key point of this investigation is to characterize new reviews automatically. To start with, features selected out of all the word roots appearing in the comments were used to train the system according to known machine learning algorithms. Next, critical words determining positive or negative sense were extracted. Another strategy was attempted eliminating common terms and dealing only with the significant class-determining words to build vocabulary with them. Aparts from linear approach, vector based feature sets were prepared out all or some of the features. The outcomes acquired were analyzed and compared leading to important conclusions, emphasizing the importance of feature selection in text classification.