Search Results (154)

Emerging digital technologies are transforming how consumers participate in financial markets, yet their benefits depend critically on the speed, reliability, and transparency of the underlying platforms. Online stock trading platforms must maintain high efficiency underload to ensure a good user experience. This paper presents performance analysis under various load conditions based on the containerized stock exchange system. A comprehensive data logging pipeline was implemented, capturing metrics such as API response times, database query times, and resource utilization. We analyze the collected data to identify performance patterns, using both statistical analysis and machine learning techniques. Preliminary analysis reveals correlations between application processing time and database load, as well as the impact of user behavior on system performance. Association rule mining is applied to uncover relationships among performance metrics, and multiple classification algorithms are evaluated for their ability to predict user activity class patterns from system metrics. The insights from this work can guide optimizations in similar distributed web applications to improve scalability and reliability under a heavy load. By framing performance not merely as a technical property but as a determinant of financial decision-making and well-being, the study contributes actionable insights for designers of consumer-facing fintech services seeking to meet sustainable development goals through trustworthy, resilient digital infrastructure. Full article

Driven by the environmental benefits associated with reduced greenhouse gas emissions, oil companies have intensified research efforts into reassessing the strategies used to meet the electrical demands of offshore production platforms. Among the various alternatives available, the deployment of onshore–offshore interconnections via High-Voltage Direct Current (HVDC) transmission systems has emerged as a promising solution, offering both economic and operational advantages. In addition to reliably meeting the electrical demand of offshore facilities, this approach enables enhanced operational flexibility due to the advanced control and regulation capabilities inherent to HVDC converter stations. Based on the use of interconnection through an HVDC link, aiming to evaluate the operation of the electrical system as a whole, this study focuses on evaluating dynamic events using the PSCAD software version 5.0.2 to analyze the direct online starting of a large induction motor and the sudden loss of a local synchronous generating unit. The simulation results are then analyzed to assess the effectiveness of both Grid-Following (GFL) and Grid-Forming (GFM) control strategies for the converters, while the synchronous generators are evaluated under both voltage regulation and constant power factor control operation, with a particular focus on system stability and restoration of normal operating conditions in the sequence of events. Full article

Objective: Family members of individuals with spinal cord injury often take on caregiving responsibilities, which can lead to caregiver burden. One factor that can mitigate the adverse effects of caregiving, such as caregiver burden, is receiving social support. Caregivers can obtain support from people they meet in person (in-person support) and on social media platforms (online support). The current cross-sectional correlational design study investigated the moderating effect of in-person and online support on the association between relationship quality, caregiver competence, caregiver distress, and caregiver burden (dependent variables). Methods: Family caregivers of an individual with spinal cord injury (n = 115) completed an online survey assessing relationship quality, competence, distress, burden, and in-person and online supports. Results: Moderation analyses showed that the negative associations between relationship quality and physical burden (B = −0.58; p = 0.019) and caregiver competence and physical burden (B = −0.73; p = 0.013) were more pronounced at higher levels of online social support. Furthermore, the magnitude of the negative associations between relationship quality and emotional burden (B = −0.52; p < 0.001) and caregiver competence and emotional burden (B = −0.34, p = 0.012) were more pronounced at higher levels of in-person social support. Moderation analyses also revealed that the positive association between distress and social burden (B = 0.47; p = 0.029) and emotional burden (B = 0.26; p = 0.045) were stronger when caregivers reported higher levels of online support. Conclusions: In-person and online support can buffer some aspects of caregiver burden on caregiver well-being. While online support is usually considered beneficial, greater online engagement may contribute to higher levels of burden when the distress is high. It is possible, however, that caregivers who are more distressed engage more with online media to receive support. Full article

This study examines the use of digitalized educational solutions among students in higher education institutions (HEIs). Drawing upon theories of technology, digitalization, and education, we analyze the suitability of different digitalization solutions for students in HEIs. Educational organizations that apply different digitalized technologies provide customizable platforms for authoring and disseminating multimedia-rich e-education and smart education. However, pedagogical practices indicate several gaps between the level of HEI digitalization achieved and its suitability for HEI participants. Thus, we analyze the state of various digitalized technologies in HEIs and their suitability for meeting students’ expectations. The results of our research show that students most highly rate modern educational methods such as practical learning supported by access to digitized materials via websites, social networks, and smartphones while assigning a lower rating to the use of classic education, supported by digital textbooks and traditional technologies such as Skype, Zoom, podcasts, and online videos. This study has several theoretical implications, among which is the need to further develop highly digitized materials and purpose-designed digitized solutions for individual areas and specific educational purposes. The practical implications indicate the need to expand the use of website networks, smartphones, and smart table solutions in modern educational practices in HEIs. Full article

The rapid expansion of digital communication platforms has created new spaces for antisocial, manipulative, and emotionally detached behaviors. While psychopathy has been extensively studied in clinical and forensic settings, its digital manifestation, referred to as cyberpsychopathy, remains conceptually underdefined. This integrative review aimed to synthesize empirical research exploring psychopathy and aversive personality traits in online contexts to identify key conceptual domains and propose a preliminary definition. A systematic search across five databases yielded 35 peer-reviewed studies meeting the inclusion criteria. Using a biopsychosocial framework and thematic synthesis, six interrelated domains were identified: online behaviors (e.g., trolling and deception), online environments (e.g., anonymity and reward mechanisms), sociodemographic factors (e.g., age and gender), personality traits (e.g., psychopathy and narcissism), psychological factors (e.g., emotion dysregulation and low self-esteem), and motivations (e.g., dominance and emotional compensation). These domains interact to shape how psychopathic tendencies manifest online. Most studies were of moderate-to-high methodological quality, though variability limited direct comparisons. We propose cyberpsychopathy as a multidimensional construct representing the expression of aversive traits facilitated by digital affordances and psychological vulnerabilities. This review provides a foundational framework for understanding cyberpsychopathy and underscores the need for empirical validation and the development of assessment tools suited to digital behavior in both clinical and forensic settings. Full article

This study explores how system-based and cognitive-based factors affect platform trust and its role in the actual use of PayLater services (buy now, pay later or BNPL) in Indonesia and Malaysia. PayLater, a fintech innovation, provides fast and convenient payment options through online platforms. By incorporating platform trust into the technology acceptance model (TAM), the research investigates whether borrowing intention acts as a mediator between platform trust and actual usage. Utilizing a quantitative approach with purposive sampling, data were gathered from 106 respondents in Indonesia and 169 in Malaysia, with 62 and 85 respondents meeting the criteria, respectively. Partial least squares (PLS) analysis indicates notable differences in how Indonesian and Malaysian users perceive platform trust, while the effect of platform trust on borrowing intention remains consistent across both nations. Borrowing intention emerges as a crucial factor influencing the actual use of PayLater services. The results offer important insights into the adoption of fintech services in emerging markets, highlighting the significance of platform trust in shaping user behavior. This research provides practical suggestions for fintech providers to improve platform trust and user engagement in cross-country scenarios. Full article

The “GeoGecko” project stands as an innovative effort in both technical and educational advancements, focusing on creating educational materials grounded in experiential learning principles with a strong gamification framework. This report provides a detailed account of the project’s development, leveraging e-learning components to create an engaging and immersive online program specifically designed to meet the expectations and needs of today’s high school and university students. Through a structured methodology, the study implemented gamified learning elements to assess their effectiveness. In addition to describing the development of the project, it also examines the teaching methods applied and the outcomes observed. Drawing on feedback from learners, the report highlights the program’s practical impact, effectiveness, and the lessons learned during its implementation. Results indicate that the platform successfully enhances student motivation, with higher engagement levels observed among younger participants compared to older learners. By sharing these insights, the “GeoGecko” project aims to contribute to the growing body of knowledge on integrating serious games and gamification into education. Full article

The development of higher education worldwide must be integrated in the context of sustainable development in order to ensure environmental sustainability, social sustainability, and economic sustainability. Knowing that the digitalization process within higher education institutions is continuously expanding, while the digital tools and online learning environments enhance accessibility, flexibility, and efficiency, the purpose of the present paper is to highlight how the use of e-Learning platforms can help sustainable education development from the point of view of students from two universities: a university from Romania and a university from the USA. In order to reach this objective, a quantitative research method was used, aiming to identify the students’ opinion on a series of facilities offered by e-Learning platforms that serve as the learning process. Data processing and analysis were conducted by means of specific tests supplied by the SPSS software. The obtained results showed that Moodle users spend approximately 26% more time on the platform than Blackboard users, with a small effect size (d = 0.284), while non-engineering students spend approximately 45% more time on the e-learning platform than engineering students, also with a small effect size (d = 0.458). The evaluation of the efficacy of different educational resources varies based on the e-learning platform used, with a large effect size found for editable files (d = 1.017) and PPT or similar formats (d = 1.2). Also, the efficacy of various applications on the e-learning platform varies by platform type, with a large effect size observed for two-way student–teacher communication (d = 0.819), self-assessment grid tests with immediate feedback (d = 1.072), synchronous online meetings with teachers (d = 1.117), and access to information from previous years (d = 0.89). We conclude that institutions should prioritize platform adaptability and student engagement strategies when implementing e-learning solutions for sustainable development. Full article

Type 1 diabetes (T1D) is a chronic disease that influences all health aspects. The self-determination theory (SDT) suggests that three psychological needs of competence, autonomy, and relatedness are necessary for motivation to engage in healthy behaviors. Through medical specialty camps, these needs can be met by educating campers on how to manage T1D and realize they are not alone. The volunteer-based, five-day, inaugural tween–teen camp for youth with T1D was held on the campus of a university. The entire camp experience was engineered around the three basic needs described by the SDT. These needs were promoted by physical and educational activities and meeting friends. The Basic Psychological Needs and Frustration Scale was administered as a pre-, post-, and follow-up test. Two of the four measures were significant, the autonomy pretest (M = 3.93; SD = 0.75) to posttest (M = 4.49; SD = 0.56), with t(25) = −6.258; p ≤ 0.001) and relatedness pretest (M = 4.31; SD = 0.79) to posttest (M = 4.53; SD = 0.49), with t(25) = −2.168; p = 0.040; however, mean scores declined at the 3-month follow-up. Campers’ blood glucose levels were collected through an online platform that allowed staff to monitor blood glucose levels, with the week’s average being 150 mg/dL, and almost 71% remaining in the TIR. The results can be helpful for practitioners who want to use the SDT to structure and examine the effectiveness of medical specialty camps for youth with T1D. Full article

A Buck converter in the DC microgrid is often used to transform high DC voltage to meet the requirements of low voltage loads, where electrolytic capacitors are commonly regarded as the most vulnerable components. A lot of studies have shown that equivalent series resistance (ESR) is the best health indicator for electrolytic capacitors, which means that it is significant to monitor the variation in ESR values for health evaluation. This paper presents a non-intrusive online ESR estimation method of the output capacitor for a Buck converter based on inductor current ripple fitting. In this method, only output voltage is sampled and inductor/capacitor current ripple is fitted by use of the characteristics of output voltage ripple. ESR calculation is implemented based on the orthogonality of the voltage ripple and the fitted current ripple, which has high-precision and anti-noise characteristics. Compared to existing methods, the proposed scheme does not require additional current sensors or high-precision trigger sampling devices, making it a cost-effective solution. Based on the proposed scheme, accurate ESR estimation is achieved for both continuous conduction mode (CCM) and discontinuous conduction mode (DCM). An experimental ESR monitoring system platform is built and experimental estimation results are provided to verify the effectiveness and the precision. Full article

The phenomenal growth of digital learning platforms has brought new learner engagement and retention challenges to higher education. This study proposes a framework that integrates game mechanics—leveling systems, badges, and timely feedback—with artificial intelligence (AI)-driven personalization to meet the challenges of enhanced adaptability, motivation, and learning outcomes in online environments. Key design elements were identified through literature reviews and consultations with instructional design experts, leading to the development an adaptive learning platform prototype. The prototype underwent an eight-week pilot study with 250 Prince Sattam Bin Abdulaziz University (PSAU) students randomly assigned to a control group (non-adaptive system) or an experimental group (adaptive system). Data sources included pre- and post-tests, platform engagement analytics, and learner perception surveys. The results showed that the adaptive group outperformed the control group in the post-test scores (M = 85.2, SD = 6.4 vs. M = 78.5, SD = 7.2) and motivation levels (M = 4.2, SD = 0.7 vs. M = 3.6, SD = 0.8). Additionally, 82% of the adaptive group achieved mastery-level performance compared to 64% in the control group. These findings demonstrate the potential of integrating game mechanics and AI-driven personalization to transform digital learning, offering a roadmap for scalable, data-driven adaptive platforms. Future research will address long-term retention and diverse subject applications. Full article

In recent years, the global economy has experienced significant shifts, leading to a trend of consumption downgrading. Amid economic pressures and uncertainties, consumers are increasingly turning to cost-effective shopping methods. The COVID-19 lockdowns further accelerated the growth of e-commerce platforms, presenting both opportunities and challenges for sales. Electronic commerce has played a crucial role in enhancing the sales of agricultural products with regional characteristics in China, thereby opening new channels for farmers. This article utilizes tangerines, particularly popular in Zhejiang Province, as a case study to explore e-commerce reviews and assist merchants in delivering more satisfactory products. The analysis of tangerine reviews revealed that customers primarily focused on the taste, service, quality, and price. By applying the latent Dirichlet allocation (LDA) topic model, comments were categorized into four themes: ‘quality’, ‘service’, ‘price’, and ‘flavor’, with key terms identified for each theme. Through sentiment analysis using SnowNLP and bidirectional encoder representations from transformers (BERT), it was found that online shoppers generally expressed positive sentiment toward tangerines. However, there was also some negative feedback. These findings are of paramount importance for businesses aiming to meet consumer demands. The study acknowledges certain limitations including the reliability of data mining and the accuracy of Chinese corpus analysis. Future research could benefit from employing more precise language models to enhance the analysis, ultimately improving the consumer shopping experience and aiding businesses in service improvement. Full article

Most of today’s educators are in no shortage of digital and online learning technologies available at their fingertips, ranging from Learning Management Systems such as Canvas, Blackboard, or Moodle, online meeting tools, online homework, and tutoring systems, exam proctoring platforms, computer simulations, and even virtual reality/augmented reality technologies. Furthermore, with the rapid development and wide availability of generative artificial intelligence (GenAI) services such as ChatGPT, we are just at the beginning of harnessing their potential to transform higher education. Yet, facing the large number of available options provided by cutting-edge technology, an imminent question on the mind of most educators is the following: how should I choose the technologies and integrate them into my teaching process so that they would best support student learning? We contemplate over these types of important and timely questions and share our reflections on evidence-based approaches to harnessing digital learning tools using a Self-regulated Engaged Learning Framework we have employed in our research in physics education that can be valuable for educators in other disciplines. Full article

Background/Objectives: Obesity remains a global health challenge. Many commercial online weight loss programs are available, and they have advantages in terms of scalability and access. Few of these programs have been evaluated for effectiveness in a real-world context. This study reports on the weight loss achieved, platform engagement, and characteristics of successful weight loss predictions in subscribers to the Interval Weight Loss (IWL) program. The Interval Weight Loss program promotes intermittent restricted eating in addition to lifestyle changes in diet composition, exercise, and sleep. Methods: Data for 1705 adults subscribing to the program for >30 days between 2019 and 2024 were included in the analysis. A linear mixed model with polynomial terms was used to model weight loss over time with interaction terms for gender and age. Survival analysis was used to model the proportions and time frame of those meeting 2%, 5%, and 10% weight loss targets and the proportion meeting their goal weight. The focus of the analysis was on the effect at 365 days. Descriptive data from a subset of participants (n = 205) who completed a questionnaire about change in lifestyle habits and mood are also presented. Results: Of those who stayed in the program for at least 365 days, 25.4% achieved their goal weight, 17.6% achieved a 10% weight loss, and 62% achieved a 5% weight loss. By 49 days, 50% had lost 2% of their weight. Significant interactions indicated that males and females in their 60s and 70s were the most responsive to the program. Conclusions: The online commercial Interval Weight Loss platform based on intermittent restricted eating resulted in significant weight loss in a cohort of subscribers in a real-world setting. Full article

Suzhou classical gardens, as a unique form of urban green space in China, not only embody rich historical and cultural heritage but also showcase distinctive natural landscapes, exerting a profound impact on modern mental health. This study employs text mining and content analysis methods to qualitatively explore online comments about Suzhou Gardens, which were collected using the Octopus Collector program to mine public reviews from the travel review platform Ctrip. These online reviews were further combined with questionnaire survey data to quantitatively analyze public preferences among different gardens and their restorative experience characteristics. We utilized the ROST CM6 software for high-frequency word extraction, semantic network analysis, and sentiment analysis to reveal the emotional perceptions of the public towards these gardens. The sentiment analysis results indicate that a majority of online comments express positive emotions, frequently mentioning words such as “tranquil”, “quiet”, and “serene”, highlighting the significant psychological comfort these spaces provide. Additionally, through one-way ANOVA and Pearson correlation analysis, we found significant differences in emotional and cognitive dimensions among different gardens, which are closely related to specific spatial factors such as landscape element diversity, visual scale, and types of greenery. These findings suggest that the spatial characteristics of Suzhou Gardens play a crucial role in shaping visitors’ emotional responses. Based on these insights, we proposed a series of design recommendations aimed at enhancing the overall image and healing functions of Suzhou Gardens. The findings of this study not only enrich the theoretical framework of healing landscape design but also provide valuable insights for the practical application of these principles in modern urban green space design. The research underscores the importance of combining functionality with aesthetic elements to meet the psychological needs of contemporary society. Full article