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Robust coherent and incoherent statistics for detection of hidden periodicity in models with non-Gaussian additive noise
We address the issue of detecting hidden periodicity when the signal exhibits periodic correlation, but is additionally affected by non-Gaussian noise with unknown characteristics. This scenario is common in various applications. The conventional approach for identifying periodically correlated (PC) behavior involves the frequency domain-based analysis. In our investigation, we also employ such an approach; however, we use a robust version of the discrete Fourier transform incorporating the Huber function-based M-estimation, unlike the classical algorithm. Building upon this approach, we propose robust coherent and incoherent statistics originally designed to identify hidden periodicity in pure PC models. The novelty of this paper lies in introducing robust coherent and incoherent statistics through the application of the robust discrete Fourier transform in classical algorithms and proposing a new technique for period estimation based on the proposed methodology. We explore two types of PC models and two types of additive noise, resulting in PC signals disturbed by non-Gaussian additive noise. Detecting hidden periodicity in such cases proves to be significantly more challenging than in classical scenarios. Through Monte Carlo simulations, we demonstrate the effectiveness of the proposed robust approaches and their superiority over classical. To further substantiate our findings, we analyze three datasets in which hidden periodicity had previously been confirmed in the literature. Among them, two datasets correspond to the condition monitoring area, being a main motivation of our research.
Journal Article
From Programming to Products: Softalk Magazine and the Rise of the Personal Computer User
In the 1980s, the user emerged as a distinct class of personal computer owner motivated by instrumental goals rather than the exploratory pleasures of hackers and hobbyists. To understand the changing values and concerns of microcomputer owners, we analyzed 1,285 reader letters published in Softalk magazine between 1980 and 1984. During this period, a preoccupation with programming was displaced by discussions of software applications, products, and services. This transition illustrates the separation of users from hobbyists, reflecting changes in the software industry and attitudes toward amateurism, professionalization, gender, and expertise.
Journal Article
Organizational Learning Management System Application via Micro PC Hardware: A Case Study in Kyrgyzstan
In the current work, systems based on mini/micro PCs that can support the corporate learning management practices have been evaluated. As a learning management system, the Moodle platform was chosen. The evaluation was based on the end users' experience. For measurement, carried out in three dimensions, a questionnaire was distributed among students enrolled in the blended course, offered with online support. According to results of the study, the installation of Moodle on micro PC was evaluated as slow. However, students agree that given the price of the device, it can be used as an alternative for the existing version of LMS used in the university. Ease of use of the system, working on micro PC, was also evaluated lower compared to the one on the server. In addition, students evaluated the security on the Moodle version installed on the device higher compared to the one in use.
Journal Article
