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The paper considers the problem of feature selection in learning using privileged information (LUPI), where some of the features (referred to as privileged ones) are only available for training, while being absent for test data. In the latest implementation of LUPI, these privileged features are approximated using regressions constructed on standard data features, but this approach could lead to polluting...
Emotional Intelligence (EI) has gained a lot of prominence in recent decades in the area of management. Its impact has been studied in the areas of managerial effectiveness, leadership skills, coping with stress etc. But there are very few studies which look at the relationship of different aspects of EI with different components of interpersonal motivations and behaviours of employees working in...
We propose a recursive singular value decomposition (SVD)-based fuzzy extreme learning machine (RSVD-F-ELM) for the online learning in classification or regression analysis. By adopting the same architecture and operation as fuzzy extreme learning machine (F-ELM), which is originally designed for the batch learning, and replacing the Moore-Penrose generalized inverse in F-ELM with a recursive SVD-based...
Facial age estimation is an important problem in the field of computer image processing. Because of the difficulty of data collection, one of the most challenges of facial age estimation is that there are not sufficient training data. Label distribution learning is an effective method to address this problem, where its motivation is that facial aging information on adjacent ages can be introduced...
This article selects teachers of primary and secondary school as the objects, from both district A (central urban area) and district B (eastern coastal rural area). We use questionnaire method to collect data about ICT of teachers in primary and secondary schools and influencing factors, and then use statistical methods of independent samples t-test and regression analysis to study the influencing...
At present, several studies exist describing the relevance of human factor in air transport with main focus on pilots and flight safety. Within such studies, monitoring of physiological functions is used. There are lot of physiological parameters and methods of their assessment; however, they are mostly based on principles originating from clinical practice. Yet, sensitivity and specificity of these...
In order to overcome the low accuracy defect of the traditional theoretical line losses calculation method in distribution system, an intelligent calculation method based on improved minimum enclosing ball vector machine (MEBVM) is proposed. In this intelligent calculation method, the theoretical line losses calculation is abstracted into multiple regression analysis. All kinds of line losses impact...
Ubiquitous social networks have in recent years become significant for sharing of content generated in online video platforms. Our work investigates how the predictability of video sharing is associated with the underlying social network of the initial sharer of the video and the context of the media platform it was uploaded. In particular we combine user-centric data from Twitter with video-centric...
Multilayer perceptron (MLP) based artificial neural network (ANN) equalizers, deploying back propagation (BP) training algorithm, have been profusely used for equalization earlier. However this algorithm suffers from slow convergence rate, depending on the size of network. In this paper, Levenberg-Marquardt and Scaled Conjugate algorithms are proposed to train an MLP based ANN for least square (LS)...
Human-crowd density estimation problem has always been difficult when the scenario is affected by strong perspective distortion and high occlusion. However, this difficulty can be mitigated by the indirect counting approach, i.e. counting them without actually detecting them. Based on this approach, Qing Wen et al. proposed a method relies on the texture features extraction using Gabor filters and...
Breadth-First Search (BFS) is widely used in real-world applications including computational biology, social networks, and electronic design automation. The most effective BFS approach has been shown to be a combination of top-down and bottom-up approaches. Such hybrid techniques need to identify a switching point which is conventionally found through expensive trial-and-error and exhaustive search...
This paper describes a mathematical model for the calciner outlet temperature via regression analysis, aim to the outlet temperature control of calciner. Based on the analysis of cement production, we find the tertiary air temperature, coal feeding and raw material feeding may affect the calciner outlet temperature. Firstly, we provide a Single-Input and Single-Output (SISO) mathematical model and...
This article proposes two modifications of a new unsupervised method of word segmentation consisting of three phases: Evaluation, Selection, and Adjustment (ESA), which was presented in our early paper. Lowest Relative Value (LRV) is the core algorithm in ESA The whole method has only one parameter (the exponent in LRV) that can be approximately predicted by the empirical formulae. In this article,...
Based on 1,130 valid questionnaires with new employees, this paper explores the mediating effect of person-organization fit between organizational socialization and work performance of new employees from the perspective of interaction between an organization and its new employees through factor analysis, descriptive statistics, correlation analysis, second-order confirmatory factor analysis, multiple...
In this paper we explore the possibility of automatic model selection in the supervised learning framework with the use of prediction intervals. First we compare two families of non-parametric approaches of constructing prediction intervals for arbitrary regression models. The first family of approaches is based on the idea of explaining the total prediction error as a sum of the model's error and...
Automatic tagging of music has mostly been treated as a classification problem. In this framework, the association of a tag to a song is characterized in a “hard” fashion: the tag is either relevant or not. Yet, the relevance of a tag to a song is not always evident. Indeed, during the ground-truth annotation process, several annotators may express doubts, or disagree with each other. In this paper,...
The amount of download prediction or forecast is a statement about the way things will happen in the future, often but not always based on experience or knowledge. While there is much overlap between prediction and forecast, a prediction may be a statement that some outcome is expected, while a forecast may cover a range of possible outcomes. Although guaranteed information about the information is...
This paper proposes a new method named Sparse Regression Analysis (SRA) for object representation and recognition. In SRA, ℓ1-norm minimization is combined with regression analysis to represent the input signal. The discriminative ability of SRA derives from the fact that the subset which most compactly expresses the input signal is activated in the regression analysis. To achieve a further improvement,...
Taking 22 Chinese Taibei men volleyball players as the subjects, we have tested 16 physical quality indexes related to the players' leaping abilities. A “0–1 program” is used to filter the tested figures according to such indexes and the selected ones will be examined by multiple regression analysis to establish the regression model. It has been tested that this model is of statistical significance...
SPSS software is used to analyze the statistical results of the investigation on the gender role and job performance of 485 female employees across the country. This paper discussed the distribution of the female gender role and finds out the significant differences in job performance between different gender roles and finds out that the level of masculinity is positively related to the job performance...
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