On-line Strategy Research Articles

Sustainable Strategies for Teaching and Learning Online

Investigating students’ lived experiences of online learning can inform us on how best to teach them. In this paper, we harness the insights gained from pandemic teaching and learning to inform sustainable approaches. Theorized in relation to Ben-Eliyahu’s sustainable learning in education (SLE), this article offers insight into what tertiary teachers can do to support students with sustainable strategies, as well as how students can develop long-term learning strategies. We draw upon the research on the perspectives and experiences of New Zealand university students studying online in 2020 to inform SLE in online teaching and learning in the long term. The researchers collaborated with student associations to undertake a survey exploring the students’ experiences of online learning. There were 952 valid survey responses from all 8 New Zealand universities, complemented by 20 individual interviews and 9 focus groups involving 43 student participants, both on and offshore. Our findings indicate that students regard support, communication, and engagement as key areas where they experienced challenges or helpful practices, and where there are sustainable directions for future teaching and learning. We propose support that institutions can provide to both students and staff for sustainable strategies.

온라인 쇼핑 추천서비스 성공 요인

In this study, we aimed to identify the success factors of recommendation services that affect online shopping satisfaction and loyalty. Based on literature review, we identified nine preliminary success factors: personalization, freshness, unexpectedness, variety, reliability, usefulness, discoverability, popularity, and ease of use. Then we collected and analyzed a total 473 data from Korea and China, and further compared the results of cultural differences between the two countries. The results of the analysis are as follows: First, personalization, variety, usefulness, and ease of use were found to be common success factors in terms of satisfaction and loyalty, while unexpectedness, reliability, and popularity were not. Second, the success factors of recommendation services differed in both countries due to cultural differences between Korea and China. In particular, in Korea, only ease of use of recommendation services can directly affect loyalty, so it is difficult for recommendation services alone to lead to continuous purchase behavior among consumers. The results of this study can be used as an empirical basis for global expansion strategies of Korean and Chinese online and mobile e-commerce platforms that want to expand their sales networks to neighboring countries.

COVID-19 Vaccine Booster Hesitancy among Hispanic Adults: A Cross-Sectional Study from the Puerto Rico Community Engagement Alliance against COVID-19 Disparities (PR-CEAL).

Hispanic/Latino communities have suffered a disproportionate burden of the COVID-19 pandemic. Although Puerto Rico has one of the highest COVID-19 primary series vaccination rates nationwide, this estimate contrasts with the reported booster doses' low uptake. This study aimed to assess health belief correlates of COVID-19 vaccine booster uptake. Using a convenience sampling approach, the Puerto Rico-Community Engagement Alliance (PR-CEAL) conducted a cross-sectional study where 787 participants were recruited using online and in-person strategies between December 2021 and February 2022. Participants were adults 18 years or older, Spanish-speaking, and residents of Puerto Rico. The Health Belief Model was used to evaluate attitudes and beliefs. A total of 784 participants were used in this analysis. Adjusted Poisson regression models were used to estimate prevalence ratios (PR) and 95% confidence intervals (CI) of booster refusal. Overall, 22% of participants refused the vaccine booster or had not gotten it yet. Adjusted models showed that (i) participants who disagreed that getting the booster dose either made them feel less worried about COVID-19 or (ii) felt that the vaccine decreased their chances of getting COVID-19 presented higher booster-refusal prevalence ratios (PR = 4.20, 95% CI: 3.00, 5.90; PR = 3.70, 95% CI: 2.64, 5.18). Moreover, participants that (iii) reported having concerns for booster side effects [PR = 2.47; 95% CI = 1.73, 3.51], (iv) booster efficacy [PR = 2.50; 95% CI = 1.75, 3.58], and (v) booster safety [PR = 2.80; 95% CI = 1.96, 3.99] were significantly more likely to refuse the booster. In conclusion, booster vaccination refusal was associated with lower perceived vaccine benefits and greater barriers among adults in Puerto Rico. These results informed the development of PR-CEAL's targeted community outreach strategies and public health campaigns to increase booster vaccine uptake.

Enhancing non-profit engagement: the extended model of webpage engagement and adoption for strategic management

This paper examines the study of Non-Profit Organization’s (NPOs’) webpages through the Strategic Online Communication Approach (SOCA) context to underpin public engagement. Although it can be argued that social networking sites such as Facebook or Twitter have a significant role in interactive online engagement, it is often webpages that have the critical role in creating engagement in the initial (and arguably most important) stage of opening dialog. In the SOCA context NPOs’ webpages need to be strategically planned and aligned with the NPOs goals and targeted to various stakeholders such as the general public, volunteers and donors. In general terms, this research resulted in a sequential model called EMEA (Extended Model of Webpages Engagement and Adoption) with three levels (information, interaction, and action). The EMEA model shows the efficiency and maturity of the webpages, indicating the level of engagement that should be possible, to therefore improve relationships with the public and obtain better results. Results show that the more ‘ways to help’ an NPO presents on its webpage, the greater the level of potential engagement (as different options to collaborate, convey trustworthy information, and control content are evident). Finally, this research showed that the greater engagement achieved by NPOs, the better the likely results and therefore the effective application of EMEA can explain and even predict success for NPOs. This paper only addresses web pages, and therefore further research is needed to clarify the role of Social Networking Sites (SNS) for high interactivity. Secondly, although EMEA is able to explain and even predict the levels of engagement, it is not evident that it necessarily occurs. Finally, although EMEA is applied correctly, it does not guarantee that NPOs are managing communication in the context of SOCA, since a multi-channel online strategy is required.

A Research Methodology Connecting Meta-analysis and the Online Tools for the Budding Medicos: A Review

This effort is intended to investigate a research methodology that links meta-analysis with an online strategy for keyword generation and to expand the field of study for future researchers. A thorough investigation was conducted before collecting the data, employing meta-analysis, research synthesis, and integration into the available literature. The results from the research integration were then compared to the real results to see if they were comparable, and based on that comparison, the final results were recorded.

Q-learning based energy management strategy for a hybrid multi-stack fuel cell system considering degradation

The use of multi-stack fuel cells (FCs) is attracting considerable attention in electrified vehicles due to the added degrees of freedom in terms of efficiency and survivability. In a multi-stack FC hybrid electric vehicle, the power sources (FCs and the battery pack) have different energetic characteristics and their operation is influenced by the performance drifts caused by degradation. Hence, efficient power distribution for such a multi-source system is a critical issue. This paper proposes a three-layer online EMS for a recreational vehicle composed of three FCs and a battery pack. In the first layer, two online estimators are responsible for constantly updating the characteristics of each FC and the battery to be used by the power distribution algorithm. In the second layer, a rule-based method is developed to improve the calculation speed of the power distribution algorithm by deciding when it should be activated. The last layer performs the power distribution between FCs and battery using a model-free reinforcement learning (RL) algorithm called Q-learning. The proposed RL-based EMS attempts to meet the requested power while minimizing the costs of hydrogen consumption and degradation of all power sources. To justify the performance of the proposed strategy, a comprehensive benchmark with an offline EMS and two online strategies is performed under two driving cycles. In comparison with the online strategies, the proposed method based on RL reduces the defined trip cost up to 11.5 % and 13.08 % under the Real driving cycle while having a higher cost than the offline strategy by 4.78 %.

A Knowledge Discovery Process Extended to Experimental Data for the Identification of Motor Misalignment Patterns

The diagnosis of misalignment plays a crucial role in the area of maintenance and repair since misalignment can lead to expensive downtime. To address this issue, several solutions have been developed, and both offline and online approaches are available. However, online strategies using a small number of sensors show a higher false positive rate than other approaches. The problem is a lack of knowledge regarding the interrelations of a fault, disturbances during the diagnosis process, and capable features and feature vectors. Knowledge discovery in database is a framework that allows extracting the missing knowledge. For technical systems, optimal results were achieved by aligning (partially) automated experiments with a data mining strategy, in this case classification. The results yield a greater understanding of the interrelations regarding parallel misalignment, i.e., feature vectors that show good results also with varying load and realistic fault levels. Moreover, the test data confirm a specificity (range 0 to 1) for classification between 0.87 and 1 with the found feature vectors. For angular misalignment, potential vectors were identified, but these need further validation with a modified experiment in future work. For the study, two induction motors with 1.1 kW and 7.5 kW were considered. Furthermore, the findings were compared with additional motors of the same rated power. The findings of this work can help to improve the implementation of sensorless diagnostics on machines and advance the research in this field.

Relationship between Internet Self-efficacy, Information Literacy, and Digital Nativity, and Online Information Searching Strategies among Public University Students in Hebei, China

Relationship between Internet Self-efficacy, Information Literacy, and Digital Nativity, and Online Information Searching Strategies among Public University Students in Hebei, China

Stress and Coping Strategies of Online Nursing Practicum Courses for Taiwanese Nursing Students during the COVID-19 Pandemic: A Qualitative Study.

The coronavirus disease (COVID-19) pandemic has resulted in significant changes in nursing education. Maintaining social distance could slow down the spread of COVID-19, and it was necessary, but it significantly reduced students' hands-on clinical practice experience in healthcare settings. Traditional classroom teaching in schools has transitioned to distance or online learning methods, which significantly reduced students' hands-on clinical practice experience in healthcare settings. Although distance education had been implemented for a long time, there are many problems and challenges to be resolved. The experiences and needs of nursing students in remote clinical training urgently require further understanding. To understand the stress and coping strategies of online nursing practicum courses for Taiwanese nursing students during the COVID-19 pandemic. A qualitative research approach with purposive sampling was supplemented by snowball sampling. Semi-structured interviews were conducted, and the data were collected following the eight-step process outlined by Waltz, Strickland, and Lenz (2010). The participants were 12 nursing students on a two-year nursing RN-to-BSN program at a university in Eastern Taiwan, consisting of 11 females and 1 male student. The stress and coping behaviors of nursing students consist of four main themes, each with three subthemes, including "urgent changes", "the gaps between online courses and practical operations", "mixed feelings of joy and anxiety" and "unexpected gains". The pandemic has impacted nursing students' learning and living. Engaging in online nursing practicum brought about significant stress; nevertheless, students employed various coping strategies to navigate through this challenging period. The findings of this study would also help nursing educators understand the learning gaps in clinical practicum among students.

Online Schedule Randomization to Mitigate Timing Attacks in 5G Periodic URLLC Communications

Ultra-reliable low-latency communication (URLLC) in 5G networks is designed to support time-critical applications such as industrial control systems (ICSs), where user equipment (UEs) communicate with a base station (BS) with very high reliability and low latency. Most of these communications in ICSs are periodic and associated with hard deadlines. To provide a reliable service while satisfying the hard deadlines, the BS usually reserves slots and frequencies and precomputes the schedule for such UEs. The same schedule repeats over time, which makes the slots and frequencies predictable. However, an attacker can exploit this aspect and launch timing attacks disrupting specific communication, thereby, undermining the safety of the system. To mitigate such attacks, we present an online strategy that randomizes the scheduled slots and frequencies over time without violating the flow deadlines. We use Kullback-Leibler divergence to measure the randomness in the schedules generated by our strategy with reference to a hypothetical truly random strategy. We perform security analysis of our proposed strategy using Prediction Probability to measure the predictability in the slots of the generated schedules. We evaluate the performance of our strategy against a state-of-the-art baseline, and show that our strategy performs better than the baseline across all parameter settings.

A feasibility study of Online Mellow Bumps: A Turkish pilot study of an online group-based antenatal parenting intervention

BackgroundAs a result of the COVID-19 pandemic, Mellow Parenting proposed online strategies for some of their interventions. One such intervention was Mellow Bumps – becoming Online Mellow Bumps. The objective of this study was to evaluate the implementation of antenatal parenting intervention Mellow Bumps in an online format and determine if this can be done safely and without detriment to pregnant women in Turkey. MethodThe study used an exploratory study design to investigate routine evaluation data collected pre- and post-intervention. Outcomes were online feasibility, mental health symptoms (depression, anxiety and stress), maternal subjective well-being, perceived quality of relationship with baby, maternal confidence and maternal social connectivity. 128 mums-to-be took part in the intervention between January 2021 and May 2021 from a total of 21 different provinces in Turkey. Results57 pre- and post-intervention responses were eligible for analysis. This gives a response rate of 44.5% for evaluation, though the intervention completion rate was high at 89.5%, suggesting the intervention is engaging and accessible. Improvements were found for maternal stress levels, maternal subjective well-being and perceived relationship with baby. Improvements were also found for maternal confidence and maternal social connectivity. ConclusionsThis is the first study to evaluate the antenatal parenting intervention Mellow Bumps in an online format, namely Online Mellow Bumps. The online format makes the programme accessible for at-risk mothers and families, with the potential to continue reaching wider audiences beyond the pandemic who otherwise might struggle to access support. The findings show that the online group can be effective in improving mental health symptoms and mental well-being, supporting expectant mothers before the baby is born. Future research using a control group, a larger and more inclusive sample, and assessing the longer-term effects on parent and child would be beneficial.

(Un)forgotten Sex Lives During the COVID-19 Pandemic: Coping Strategies That Work and the Role of Experience.

Available literature points to a worsening trend in sexual functioning, desire, and satisfaction during the pandemic. Nevertheless, virtually no empirical research was conducted on the mechanisms of coping with the pandemic's impacts on sex life. Thus, the purpose of this exploratory study was to examine a variety of coping mechanisms and their perceived usefulness by people who have and have not tried these coping strategies to maintain and enhance their sex lives during the first year of the pandemic. The cross-sectional data were collected using an online survey methodology (N = 420; 66.9% women) and analyzed utilizing exploratory factor analysis, analysis of variance, and multiple regression. The results revealed nine factors/coping mechanisms (based on 59 items/strategies), including goal-setting strategies, risk and experimentation strategies, relational strategies, caution and logistical strategies, creativity and innovation strategies, substances and context-related strategies, online and technology strategies, diversion strategies, and educational strategies. Consistently, across all the specific coping strategies and overall coping mechanisms, people who tried them found them significantly more useful than those who had not tried these coping strategies. Moreover, a higher diversity of tried strategies per coping mechanism consistently and significantly predicted the perceived usefulness of that coping mechanism. These results emphasize the crucial role of experience with coping mechanisms and show that amidst COVID-related adversity and challenges, many people found ways to adapt their sex lives and enjoy silver-lining opportunities. This exploratory study offers promising evidence for potential sexual coping strategies during times of stress that could be informative for clinical practice and education.

HOW TO DEAL WITH BURNOUT DURING ONLINE LEARNING IN MEDICAL EDUCATION? A SYSTEMATIC REVIEW

Background: During their education, medical students face various types of stress in medical school. The COVID-19 pandemic has caused significant changes in communication. Technology improves the usage of telecommunications in medical education, making students spend more time staring at screens, tablets, and smartphones, which may affect stress and lead to burnout. This study aims to explore burnout and strategies for reducing the occurrence of burnout in students during online learning.Method: This study is a systematic review aimed at exploring the burnout phenomena in medical students doing online learning and strategies to prevent it. The journal articles were sought from the PubMed, Google Scholar, and Springerlink databases. We applied the inclusion and exclusion criteria to select the relevant journal articles. We analyze the validity and review the articles descriptively. Results: After the systematic selection of the journal articles, there are 28 full journals related to burnout and prevention strategies. The result defines Burnout as an individual's reaction to long-term work stress that lasts for a long time and can become chronic. In this article, six strategies can be used by institutions, educators, and students to help overcome the incidence of burnout during online learning.Conclusion: There is a need for a strategy carried out by institutions that provide facilities to provide emotional support to students; develop educators to prevent burnout during the learning process; apply healthy practices in preventing the eyes from doing ice-breaking between online learning sessions, and use various visual interactive learning methods to increase the interest and motivation of students to avoid burnout during online learning.

Adolescent experiences with online racial discrimination: Implications for prevention and coping.

Online aggression represents a wide range of negative experiences, including online discrimination targeting individuals based on race, but adolescent perspectives are not well-represented. We interviewed 15 adolescents regarding their experiences with online racial discrimination. After a phenomenological analysis, four main themes emerged: types of online racial aggression, processes supporting online racism, personal coping, and strategies to prevent online racial aggression. These themes provided insights into adolescent experiences, including feelings about targeted online racial discrimination, intersectionality with sexual harassment, and comfort through processing with friends. This study highlights adolescents' thoughts regarding advocacy, education, and social media reform to prevent online racial aggression. Future research should ensure that youth voices from minoritized racial backgrounds are integrated into efforts to address these critical social issues.

Inverse Modeling for Subsurface Flow Based on Deep Learning Surrogates and Active Learning Strategies

AbstractInverse modeling is usually necessary for prediction of subsurface flows, which is beneficial to characterize underground geologic properties and reduce prediction uncertainty. Considering the intensive computational effort required for repeated simulation runs when solving inverse problems, surrogate models can be built to substitute for the simulator and improve inversion efficiency. Deep learning models have been widely used for surrogate modeling of subsurface flow. However, a large amount of training data is usually needed to train the models, especially for constructing globally accurate surrogate models, which would bring large computational burden. In fact, the local accuracy of surrogate models in regions around the true solution of the inverse problem and the potential searching path of the solution is more important for the inversion processes. The local accuracy of surrogate models can be enhanced with active learning. In this work, active learning strategies based on likelihood or posterior information are proposed for inverse modeling, including both offline and online learning strategies. In the offline strategy, a pre‐trained model is utilized to select samples with higher likelihood, which can produce model responses closer to the observations, and then the selected samples can be used to retrain the surrogate. The retrained surrogate is further integrated with the iterative ensemble smoother (IES) algorithm for inversion. In the online strategy, the pre‐trained model is adaptively updated and refined with the selected posterior samples in each iteration of IES to continuously adapt to the solution searching path. Several subsurface flow problems, including both single‐phase groundwater flow and two‐phase (oil‐water) flow problems, are introduced to evaluate the performance of the proposed active learning strategies. The results show that the proposed strategies achieve better inversion performance than the original surrogate‐based inversion method without active learning, and the number of required simulation runs can also be reduced.

Rejuvenating Kenyan Academic Library Services in the post-COVID-19 era

Academic libraries in Kenya have invested heavily in subscribing to electronic resources through the Kenya Library Information Services Consortium (KLISC), an attempt has been made to install relevant technological infrastructure and to some extent ensured the utilisation of digital services and resources to meet the needs of their clientele. However, the COVID-19 pandemic posed a special challenge to physical library services. Academic institutions were forced to close down to reduce the spread of the virus and fully provide their services online. This paper explores the interventions academic libraries applied to provide their services during COVID-19 era with a view of rejuvenating library services in the post-COVID-19 era in Kenya. A systematic literature review was used a methodology for the study. The review of online published articles on academic libraries operations and services provision amidst COVID-19 pandemic was conducted with a view to identifying global interventions to help rejuvenate academic library services in Kenya in post COVID-19 era. Findings of this study shows thatglobally, academic libraries adopted varied online strategies to provide services. Some of these include, document delivery via email, use of VPN to access online resources, mobile apps, web-based live chat, interactive social media platforms and online meeting applications such as google class, google meet, zoom, webinars. The finding provides key insights to varied media utilized in library operations and services. Challenge that hindered optimum utilisation of the service include lack of adequate information technology infrastructure and devices, limited budgets, insufficient digital competences, and inadequate digital policies. This paper recommends development of library digital policies on use of digital resources, re-prioritize enhanced library budgets to increase e-services provision, build capacity of library staff and users and invest in appropriate IT infrastructure in order to reposition library services appropriately in the post COVID-19 era and beyond

Sensitivity enhancement of capillary electrophoresis-frontal analysis-based method for characterization of drug-protein interactions using on-line sample preconcentration.

Capillary electrophoresis-frontal analysis is one of the most frequently used approaches for the study of plasma protein-drug interactions as a substantial part of new drug development. However, the capillary electrophoresis-frontal analysis typically combined with ultraviolet-visible detection suffers from insufficient concentration sensitivity, particularly for substances with limited solubility and low molar absorption coefficient. The sensitivity problem has been solved in this work by its combination with an on-line sample preconcentration. According to the knowledge of the authors this combination has never been used to characterize plasma protein-drug binding. It resulted in a fully automated and versatile methodology for the characterization of binding interactions. Further, the validated method minimalizes the experimental errors due to a reduction in the manipulation of samples. Moreover, employing an on-line preconcentration strategy with capillary electrophoresis-frontal analysis using human serum albumin-salicylic acid as a model system improves the drug concentration sensitivity 17-fold compared to the conventional method. The value of binding constant (1.51±0.63) ·104 L/mol obtained by this new capillary electrophoresis-frontal analysis modification is in agreement with the value (1.13±0.28) ·104 L/mol estimated by a conventional variant of capillary electrophoresis-frontal analysis without the preconcentration step, as well as with literature data obtained using different techniques.

Digital Revolution and the Prospects for Online Political Communication

A revolution in information and communication technology has introduced social media as alternative platforms through which political parties can interact with the public. Political parties’ success in using these avenues depends on the online strategies applied. Tanzania has not been an exception in the use of social media as political parties have been using them for political activities. However, little is known regarding the way political parties have established themselves on social media platforms. Using the equalization, normalization, and hybrid perspectives as an analytical framework, this paper examines the status of Tanzania’s political parties in social media. The data obtained through the review of social media pages, key informant interviews and documentary analysis reveal that although political parties have been using social media for political activities, the profile of their social media status is low. The findings further show that social media have not altered the balance of power among political parties in Tanzania as the social media profile of opposition political parties does not significantly differ from that of the ruling party CCM as revealed by the number of their social media pages, followers and posts as well testimonies through interviews regarding social media usage. Several factors including political parties’ limited awareness of the potential of social media, the unpredictability of the political system as well as resource constraints are attributed to this status. To overcome these challenges, a call is made for policy and capacity building interventions to empower political parties and the citizenry for effective online engagement.

Experimental validation of multi-stage optimal energy management for a smart microgrid system under forecasting uncertainties

This paper proposes a Multi-stage Energy Management System (MS-EMS) for power distribution in a smart microgrid comprising a photovoltaic system (PV), an Energy Storage System (ESS), and connected to an Electrical Power Grid (EPG). The proposed MS-EMS consists of two layers, the Anticipative Layer (AL) and the Reactive Layer (RL). The AL uses a Multi-objective particle swarm optimization (MOPSO) algorithm to determine the optimal power setpoints for each source over the next 24 h based on predicted energy demand and solar power generation. The RL utilizes real-time data collection and Extremum-Seeking optimization (ES) to compensate for prediction uncertainties by adjusting the ideal power setpoints in real-time. In addition, this paper addresses both the issues of management and prediction. It introduces a forecasting system that effectively predicts the next 24 h of load demand and PV power generation using actual data, by integrating a physical model with artificial neural networks (ANN). The efficiency of the proposed MS-EMS is highlighted using experimental data collected in real-time on a physical bench in Morocco. The performances of the proposed MS-EMS system are compared with those of existing EMS strategies, including an existing industrial solution. The comparison shows that the proposed MS-EMS substantially overperforms in terms of three criteria: energy bill, battery degradation cost, and peak-to-Average Ratio (PAR). Despite forecasting uncertainties, the experimental test shows a remarkable 6% gain in the reduction of the energy bill and PAR compared to an offline strategy (where uncertainties were not considered). Furthermore, it achieved a 5% and a 3% gain in the reduction of the energy bill and PAR, respectively compared to an online strategy (focused on real-time optimization). Additionally, compared to an existing industrial solution, the MS-EMS achieves a reduction in energy bill and PAR of 9% and 56% respectively while taking into account battery degradation constraints described in this study.

تحليل تداولي لاستراتيجيات التأدب في الدردشة عبر الإنترنت التي يستخدمها طلاب اللغة الإنجليزية كلغة أجنبية في مدارس المتميزين في الأنبار

The aim of this paper is to identify the politeness strategies employed by Iraqi EFL students in Al-Anbar Distinguished Schools which is regarded an area that is infrequently investigated by scholars. To attain this aim, the participants of the study were selected from Al-Anbar Distinguished Schools, represented by 53 female students and 50 male students during the academic year (2021-2022) to be in direct and frequent online interaction (via text messages) with each other as students, and with their teachers of English language. Consequently, WhatsApp and Telegram groups were created for this online chatting. A qualitative research design was conducted whereby online text chatting was collected to ensure the data of this study. The collected data were analyzed qualitatively by using content analysis procedure based on Brown and Levinson’s (1987) model of politeness strategies. The findings of the study revealed that the participants utilized various types of politeness strategies in their communication via online chatting. Based on the calculated frequencies and percentages, Positive Politeness Strategies were the most frequently used (dominant type), then Negative Politeness Strategies, Bald On-Record and Off-Record Politeness Strategies respectively. Additionally, the findings indicated that Off-Record Politeness Strategies were used rarely by the participants of the study.