A grid-connected system, in particular, relies heavily on the generation of electricity from Renewable Energy Sources. Because of the RES\'s connection to a grid, problems with power quality have arisen. Harmonics, voltage swells, sags and other grid concerns are caused by power quality issues. As solar and wind energy are both free and environmentally beneficial, they are regarded as the finest options for remote (or rural) electricity. The combination of solar power and wind power is a reliable source of energy creating a constant energy flow by avoiding the fluctuations. But this hybrid system gives rise to complications related to power system stability. Most of the industrial loads are controlled by power electronic converters that are sensitive to power system disturbances. Hence the power quality issues diminution is more focused in recent times as it is vital in power supply industry. A number of power semiconductor devices have been developed to overcome the above power quality issues. Distributed Power Flow Controller (DPFC), which is emerged from Unified-Power-Flow- Controller is considered as the best reliable device among the others. To report these expanded issues, the authors recognized an advanced custom power device entitled Distributed Power Flow Controller. The proposed Solar-Wind hybrid energy system is studied initially with Distributed Power Flow Controller. Later the system is examined with Genetic Algorithm based ANFIS Controller for Shunt control of Distributed Power Flow Controller. The results of the investigation demonstrate DPFC with Genetic Algorithm-AdaptiveNeuroFuzzyInferenceSystem has improved achievement in conditions of harmonics reduction and voltage compensation. MATLAB/Simulink has been used to study the anticipated integrated hybrid system under unbalanced voltage situations.

Objective: To find out whether mental mindfulness predicts psychological well-being and to see what impact (gender) factors have on that connection.\nMethod: This study looked at the mental mindfulness/psychological well-being link in a sample of 150 university students. A self-administered questionnaire was used in conjunction with a quantitative research method. The study\'s results revealed a favorable connection between several aspects of mental awareness and the overall degree of psychological well-being. \nResults: There was no correlation between the observation dimensions on the mental mindfulness scale and the self-acceptance, life goals, and positive social relationships with others on the psychological well-being scale at a significance level of 0.01, according to the findings. Mental mindfulness aspects may be used to predict university students\' psychological well-being, which has been shown. Mental awareness and its investigated aspects were not found to vary significantly between men and women, according to the results. The research provides new information and knowledge that helps the decision-maker, especially the universities responsible for preparing a generation that enjoys mental health standards and the quality of life in general. It also sheds light on a set of important variables such as mindfulness, psychological well-being, and their impact on the academic work environment.\nConclusion: There are disparities between men and women on the factors (independence - personal maturity - total degree of psychological well-being) in favor of men in addition to emphasizing the distinctions between them (self-acceptance - the purpose of life - social relations - mastery of the environment).

Principal component analysis (PCA) has been well known for useful statistical techniques in many disciplines. One of the prevalent uses of PCA is the dimension reduction technique, in which a vast number of variables can be summarized into a few important variables without losing the original information. There are currently few resources for step-by-step instructions for using PCA dimension reduction techniques, particularly in the social sciences field. In this work, the PCA analysis was employed to identify the components used as items measurement in the Open Government Data (OGD) post-adoption study. Four component retention methods were utilized to assess the components: the eigenvalues, proportion of total variance, scree plot test, and the interpretability criterion. The data was garnered from 125 OGD adopters among public agencies. Nine components were extracted to represent 39 items of measurement of OGD post-adoption independent factors. This paper’s contribution is two-fold: (i) it describes the process of developing the questionnaire items to measure OGD post-adoption among public agencies using principal component analysis; and (ii) it demonstrates the use of principal component analysis to extract important factors from a set of correlated variables as a different technique to factor analysis.

This paper presents results from experiments dealing the ovalization and critical ovalization of 7005-T6 aluminum alloy round-hole tubes (7005-RHTs) with different hole diameters of 2, 4, 6, 8, and 10 mm submitted to cyclic bending. It can be observed that the cross-section of the 7005-RHT continues to ovalize to a critical value before breaking. A larger controlled curvature or hole diameter leads to a greater ovalization. In addition, the relationship between the ovalization at negative extreme curvature and number of cycles can be divided into three stages (stages I, II and III). However, most of the number of cycles are in stages I and II. Finally, the empirical formula introduced by Lee et al. in 2010 was employed and material parameters related to the hole diameter were proposed for simulating the above-mentioned relationships in stages I and II. In addition, an empirical formula was also proposed to simulate the critical ovalization-controlled curvature relationships. It was found that the experimental and simulated data agreed quite well.

This article discusses the kinematic model of a group\'s pursuit of a single goal using the parallel convergence method. The model is based on the fact that the pursuers try to adhere to pre-designed trajectories. The pursuer\'s trajectories have curvature restrictions. The initial velocity directions of the pursuers are arbitrary, which makes changes to the known method of parallel approach. In our model, the pursuers achieve the goal simultaneously. This is due to changing the lengths of the predicted trajectories in such a way as to synchronize the time to reach the goal. The change in length is due to an increase in the radius of curvature at the initial section of the trajectory.

Introduction: One of the most successful approaches to treat patients with rare diseases in a quality, timely and effective manner is to create a rare disease ecosystem. It represents a functional environment that integrates all stakeholders, procedures, and relations required for organized and effective patient treatment. This paper explores the current situation in the field of rare diseases, especially in light of the proposed ecosystemic arrangement, and drafts a blueprint for the design of a rare disease ecosystem in Slovenia. \nMethodology: The research applies a case study design, where focus groups were used to assess the state of affairs, generate ideas, and collect evidence from the field. Structured discussions were conducted with eminent experts affiliated with the leading institutions in the field of rare diseases in Slovenia. Analysis and interpretations of the data obtained were carried out by means of conventional content analysis. \nResults: Setting up a rare disease ecosystem in Slovenia would render a significant advance for patients, as it could considerably promote the coordination of healthcare treatment and facilitate extensive monitoring of the treatment parameters and outcomes. A well-organized rare disease ecosystem could convey considerable systemic benefits to evidence-informed policymaking, better utilization of resources, technological innovation, and business processes reengineering. \nConclusion: Providing quality healthcare delivery in this complex field is largely reliant on the effective integration and collaboration of all entities within the rare disease ecosystem, alignment of related systemic factors, and the direction of healthcare services to support the needs and well-being of patients with rare diseases.

Computer vision technology based on image captured device and algorithm of colorimetric parameters evaluation of milk freshness indicators was proposed. The algorithm of colorimetric parameters evaluation was realized by means of National Instruments Vision Builder for Automated Inspection.