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In [10] and [16], we proposed tools for simultaneous variable selection and parameter estimation in a functional linear model with a functional outcome and a large number of scalar predictor. We call these techniques Function-on-Scalar Lasso (FSL) and Adaptive Function-on-Scalar Lasso(AFSL). A scalar group lasso was used to fit the FSL and AFSL estimates. While this approach works well, we improve...
The article describes the factor model of Tomsk region schools functioning which was developed and investigated using the STATISTICA system. The constructed model describes an impact of different variables (context factors) on educational results of Tomsk school graduates. At the preliminary stage the most significant variables were determined, the exploratory data analysis was made using the method...
This paper is aimed at discussing several issues related to the teamwork generic competence, motivational profiles, and academic performance. In particular, we study the improvement of teamwork attitude, the predominant types of motivation in different contexts, and some correlations among these three components of the learning process. The above-mentioned aspects are of great importance. Currently,...
We present a novel approach to principal component analysis (PCA) for data expressed in terms of Atanassov's intuitionistic fuzzy sets (A-IFSs), i.e. using the degree of membership, non-membership and hesitation margin which was shown in our works to be a prerequisite for a meaningful analysis of A-IFS type data and information. This new approach to PCA for the A-IFS data is relevant for making possible...
Consumer perceived value has become increasingly important for hotel marketers and operators due to the highly competitive environment. This paper attempts to answer the following questions: (1)What dimensions do consumer perceived value involve in hotel context? (2)What's the relationship between these dimensions? A total of 202 samples were analysed with exploratory factor analysis(EFA) and confirmatory...
Context-based communication services analyze user data and offer new and novel services that enhance end user unified communication experience. These services rely on data analysis and machine learning techniques to predict user behavior. In this paper we look at topic modeling as an unsupervised learning tool to categorize user communication data for retrieval. However, modeling topics based on user...
The widespread use of positioning technologies ranging from GSM and GPS to WiFi devices, tend to produce large-scale datasets of trajectories, representing the movement of travelling entities. Several applications may benefit from mining such datasets. However, mining results only become truly useful and meaningful for the end user when the intrinsically complex nature of the movement data in terms...
Cumulative Voting (CV), also known as Hundred-Point Method, is a simple and straightforward technique, used in various prioritization studies in software engineering. Multiple stakeholders (users, developers, consultants, marketing representatives or customers) are asked to prioritize issues concerning requirements, process improvements or change management in a ratio scale. The data obtained from...
The study was to investigate the generalizability of perceived organizational support and job satisfaction as positive correlations of employee performance in China. In a study conducted, 130 matched cases of 130 employees and their 34 immediate supervisors from two large-scale state-owned enterprises were selected as participants. Standardized psychological scales measuring POS, job satisfaction,...
Reports generated by soldiers are common in time-critical military environments. Data fusion systems that attempt to process those reports must maintain the context for each set of observations to avoid inaccurate state estimates. This paper analyzes the selection and assignment of topical context under a Bayesian methodology. We present several techniques to decrease the hypothesis space and heuristics...
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