Search Results (10,433)

Deep learning (DL) has been widely applied to forecast the sales volume of household appliances with high accuracy. Unfortunately, in small towns, due to the limited amount of historical sales data, it is difficult to forecast household appliance sales accurately. To overcome the above-mentioned challenge, we propose a novel household appliance sales forecasting algorithm based on transfer learning, temporal convolutional network (TCN), long short-term memory (LSTM), and attention mechanism (called “TransTLA”). Firstly, we combine TCN and LSTM to exploit the spatiotemporal correlation of sales data. Secondly, we utilize the attention mechanism to make full use of the features of sales data. Finally, in order to mitigate the impact of data scarcity and regional differences, a transfer learning technique is used to improve the predictive performance in small towns, with the help of the learning experience from the megacity. The experimental outcomes reveal that the proposed TransTLA model significantly outperforms traditional forecasting methods in predicting small town household appliance sales volumes. Specifically, TransTLA achieves an average mean absolute error (MAE) improvement of 27.60% over LSTM, 9.23% over convolutional neural networks (CNN), and 11.00% over the CNN-LSTM-Attention model across one to four step-ahead predictions. This study addresses the data scarcity problem in small town sales forecasting, helping businesses improve inventory management, enhance customer satisfaction, and contribute to a more efficient supply chain, benefiting the overall economy. Full article

An office building in Trondheim, Norway, was used as a case study to test the influence of Predictive Control (PC) for the optimization of energy use on the employees’ thermal comfort. A predictive control was implemented in the Building Energy Management System (BEMS) by operating on the supply temperature of the radiator circuit. A questionnaire was given to the employees to evaluate to what extent the operation of the predictive control influenced their perceived thermal comfort. Several factors known to influence employees’ satisfaction (such as office type, perceived noise level, level of control, perceived luminous environment, perceived indoor air quality, adaptation strategies, well-being) were investigated in the questionnaire. The evaluation shows that the occupants rated the perceived thermal comfort as equally good compared to the business-as-usual operation. This is an important finding toward the user acceptance of such predictive control schemes. Full article

Virtual reality (VR) offers immersive visual and auditory experiences, transporting users to alternate realities. However, existing VR systems lack realistic haptic feedback mechanisms, resulting in unsatisfactory immersive experiences. In this study, we developed and tested a haptic glove that simulates realistic tactile sensations, enhancing user interaction with virtual artifacts. Our research investigates the impact of finger-specific vibrotactile feedback (FSVF) on user experience in virtual museum environments. Using a mixed-methods approach, 30 participants engaged in object-manipulation tasks in three settings: no haptic feedback, standard controller feedback, and vibrotactile glove feedback. The findings demonstrate that the vibrotactile glove approach considerably improves user accuracy, efficiency, immersion, and satisfaction compared with other traditional interaction methods. Participants completed tasks more accurately and quickly with the glove, reporting high levels of engagement and immersion. The results highlight the potential of advanced haptic feedback in transforming virtual reality technology, particularly for educational and cultural applications. Further, they provide valuable insights for designing and applying future haptic technology in immersive environments. Full article

Nearly 28,000 children, ranging from kindergarten to secondary-school age, commute between mainland China and Hong Kong for education on a daily basis. They are known as cross-border students (CBS)—those who legally hold permanent Hong Kong citizenship and attend schools in Hong Kong, but reside in mainland China, a unique population in the context of cross-border migration. Social media has reported various challenges faced by CBS, but systematic research on this population is limited. This study proposes a resilience and social capital framework to understand the psychosocial adjustments of CBS when faced with different levels of adversities. Using data from a cross-sectional survey of 445 CBS, this study examines how family and community social capital promote the self-esteem, mental well-being, happiness, and life satisfaction of CBS through individual resilience in the face of single and multiple adversities. The results of structural equation modelling suggest that family social capital serves as a significant promotive and protective factor for the self-esteem, mental well-being, happiness, and life satisfaction of CBS in the presence of both single and multiple adversities, while community social capital can promote only mental well-being of CBS in the presence of single or no adversity. Theoretical and practical implications of these findings for researchers, parents, and service professionals are also discussed. Full article

This paper aims to identify the factors that are positively or negatively impacting students’ well-being and their academic engagement. We used partial least-squares structural equation modeling (PLS-SEM) using the data collected through a questionnaire from four countries: Romania, Turkey, Slovakia, and Bulgaria. The model includes seven factors that influence the well-being of students and indirectly their academic engagement: stressors in the students’ lives; professors’ support; social support from family and friends; the students’ perceived satisfaction in their lives; engaging in activities during their leisure time; self-exploration regarding their careers; and environmental exploration regarding their careers. The results show that all factors, except for stressors and environmental exploration regarding their careers, positively influence the students’ well-being and thus their academic engagement. These findings are useful for universities professors and managers in better organizing activities to increase academic performance. Full article

This study introduces an innovative surgical approach for total knee arthroplasty (TKA) that combines kinematic alignment (KA) principles with real-time elongation of the knee ligaments through the range of motion, using augmented reality (AR). The novelty of the surgical technique lies in the possibility of enhancing the decision-making process to perform the cut on the tibia as for the KA caliper technique developed by Dr. Stephen Howell. The NextAR is a CT-based AR system that offers the possibility of performing three-dimensional surgical preoperative planning and an accurate execution in the surgical room through single-use infrared sensors, smart glasses, and a control unit. During the preoperative planning, the soft tissue is not considered and only the alignment based on bony reference is ensured. Thanks to the possibility of measuring in real time the elongation of the knee collateral lateral ligaments, the system assists the surgeon in optimizing the cut on the tibia after an accurate resurfacing of the femur as described in the KA surgical technique. The implant used in this novel approach is a medial pivot design (Medacta GMK Sphere) that allows the restoration of the physiological behavior of the software tissue and natural knee kinematics. In conclusion, this novel technique offers a promising approach to TKA, allowing personalized treatment tailored to each patient’s unique anatomy and soft tissue characteristics. The integration of KA and real-time soft tissue analysis provided by NextAR enhances surgical precision and outcomes, potentially improving patient satisfaction and functional results. Full article

Knowledge representation models that aim to present data in a structured and comprehensible manner have gained popularity as a research focus in the pursuit of achieving human-level intelligence. Humans possess the ability to understand, reason and interpret knowledge. They acquire knowledge through their experiences and utilize it to carry out various actions in the real world. Similarly, machines can also perform these tasks, a process known as knowledge representation and reasoning. In this survey, we present a thorough analysis of knowledge representation models and their crucial role in information management within the healthcare domain. We provide an overview of various models, including ontologies, first-order logic and rule-based systems. We classify four knowledge representation models based on their type, such as graphical, mathematical and other types. We compare these models based on four criteria: heterogeneity, interpretability, scalability and reasoning in order to determine the most suitable model that addresses healthcare challenges and achieves a high level of satisfaction. Full article

The increasing number of electric vehicles (EVs) necessitates the installation of more charging stations. The challenge of managing these grid-connected charging stations leads to a multi-objective optimal control problem where station profitability, user preferences, grid requirements and stability should be optimized. However, it is challenging to determine the optimal charging/discharging EV schedule, since the controller should exploit fluctuations in the electricity prices, available renewable resources and available stored energy of other vehicles and cope with the uncertainty of EV arrival/departure scheduling. In addition, the growing number of connected vehicles results in a complex state and action vectors, making it difficult for centralized and single-agent controllers to handle the problem. In this paper, we propose a novel Multi-Agent and distributed Reinforcement Learning (MARL) framework that tackles the challenges mentioned above, producing controllers that achieve high performance levels under diverse conditions. In the proposed distributed framework, each charging spot makes its own charging/discharging decisions toward a cumulative cost reduction without sharing any type of private information, such as the arrival/departure time of a vehicle and its state of charge, addressing the problem of cost minimization and user satisfaction. The framework significantly improves the scalability and sample efficiency of the underlying Deep Deterministic Policy Gradient (DDPG) algorithm. Extensive numerical studies and simulations demonstrate the efficacy of the proposed approach compared with Rule-Based Controllers (RBCs) and well-established, state-of-the-art centralized RL (Reinforcement Learning) algorithms, offering performance improvements of up to 25% and 20% in reducing the energy cost and increasing user satisfaction, respectively. Full article

Telecommunications firms face intense competition driven by rapid innovation and shifting consumer expectations. To remain competitive, companies are adopting Total Quality Management (TQM) to enhance customer satisfaction, corporate stability, and sustainability. This study examines TQM’s effects on customer satisfaction within Gulf Cooperation Council (GCC) countries’ telecommunications sector using secondary data from three firms’ quarterly reports (2019–2023). Descriptive, correlation, and regression analyses with STATA software reveal a significant increase in net promoter scores, indicating firms’ commitment to meeting evolving customer needs. Employee engagement and process management positively affect customer satisfaction, while continuous improvement practices and customer focus do not show a statistically significant influence. The research underscores TQM’s importance in fostering sustainable customer satisfaction by enabling telecom companies to adopt customer-centric strategies for achieving sustainable growth and long-term success. Aligning business processes with customer needs, especially in complaint handling, is crucial. The study advocates for implementing advanced customer relationship management (CRM) systems to better understand customer preferences. These strategic initiatives are vital for telecom firms to maintain competitiveness, enhance customer satisfaction, and contribute to the region’s overall economy. Full article

Background: Virtual reality (VR) emerges as a promising non-pharmacological intervention for managing symptoms and providing distraction during chemotherapy. This study aims to assess VR’s effectiveness on cancer-related symptoms, vital signs, and the patients’ perception of chemotherapy in lung cancer patients. Methods: A quasi-experimental study was conducted on 100 patients. Participants were allocated into an intervention group (n = 55), which experienced immersive VR, and a comparison group (n = 45), which received usual care. Data were collected through questionnaires and checklists, including feedback on the VR experience, pain, vital signs, and common cancer symptoms, assessed through the Edmonton Symptom Assessment Scale. Results: VR had a significant impact on reducing the perception of chemotherapy length. Patients reported high levels of satisfaction and tolerability. No adverse events were observed. VR did not have significant influence on pain intensity or vital signs. The only exceptions were oxygen saturation, where a significant difference (p = 0.02) was reported, and the perception of chemotherapy duration. Conclusions: As a non-pharmacological intervention, VR proves to be beneficial in minimizing the perceived length of chemotherapy sessions for lung cancer patients, enhancing their overall treatment experience. The intervention was found to be a safe, feasible, and well-accepted distraction technique. Future research should explore VR’s potential effects on a wider range of symptoms and evaluate its impact on long-term outcomes. Full article

The current talent training system for the environmental engineering major (EEM) at local colleges faces significant challenges, including undefined training objectives, an incomplete curriculum, inconsistent practical teaching platforms, and homogeneous teaching teams. To address these issues, this study introduces the ‘Four Styles’ cultivation system implemented at the EEM of Hubei Polytechnic University. This system integrates advanced environmental remediation technologies into environmental engineering education through the development of a ‘1 + multiple’ curriculum, the establishment of ‘cloud + field’ practical platforms, and the formation of a diverse ‘1 + 2’ teaching team. The effectiveness of this system was evaluated using self-assessment scores from graduates and employer satisfaction ratings. Results showed that graduates rated their application ability with an average score of 3.96 ± 0.11, with the highest scores in work ethics (4.14), lifelong self-learning (4.11), and teamwork (4.09). Employer satisfaction with graduates’ abilities averaged 81.6 ± 2.33%, with the highest ratings for work ethics (86.0%), teamwork (85.5%), and lifelong self-learning (84.7%) Despite these successes, areas for improvement were identified, including better training in analyzing engineering problems (3.79) and mastering modern tools (3.79). These findings suggest that the ‘Four Styles’ cultivation system effectively enhances the practical skills of EEM students while identifying areas for future curriculum development. Full article

The diverse backgrounds of health professions faculty often result in inconsistent teaching, clinical techniques, and feedback for students. Faculty calibration is essential for uniform, high-quality instruction. However, scheduling training sessions is challenging due to faculty availability. This study introduces a self-paced, interactive online approach to dental faculty calibration. Four self-paced online modules were developed using an interactive cloud-based platform. A variety of learning activities were interspersed throughout the module to promote active learning. A survey captured faculty’s perception of the online format. ANOVA analyses examined differences in perceived effectiveness of the online format between full-time, part-time, and adjunct faculty. The platform analytics offered insights into the faculty’s module performance. Anecdotal feedback from faculty provided evidence of behavioral changes. 94% of the faculty expressed high satisfaction with the online format. The majority of faculty agreed or strongly agreed that the online format was effective (89%), engaging (88%), and easy to navigate (84%). They highlighted the modules’ user-friendliness, flexibility, and engaging content. ANOVA analyses revealed no significant differences in perceived effectiveness of the online format between full-time, part-time, and adjunct faculty. Anecdotal feedback demonstrated that faculty were incorporating the knowledge gained from the modules into their teaching practices. This positive online experience also motivated several faculty to integrate similar online approaches into their own courses. This online approach provides a more flexible, sustainable, and interactive approach to faculty development that could be beneficial to other institutions. Full article

The Sustainable Development Goals (SDGs) have set the agenda for 2030, calling for collective global efforts to deal with climate change while seeking a balance between economic development and environmental protection. Although many countries are exploring emission reduction paths, mainly from government and corporate perspectives, addressing climate change is also an individual responsibility and requires public participation in collective action. The millennial generation constitutes the current workforce and will be the leaders in climate action for the next 30 years. Therefore, our study focuses on the Chinese millennial generation, conducting in-depth semi-structured interviews with 50 participants in qualitative research to explore their low-carbon lifestyles, the barriers, and enablers in switching to a wider range of low-carbon lifestyles. There are three main results: (1) Based on our study samples, there is an indication that Chinese millennials have a positive attitude towards transitioning to a low-carbon lifestyle. Women demonstrate a stronger willingness to adopt low-carbon behaviors in their daily household activities compared to men. However, their involvement in governance in the context of transitioning to a low-carbon society is limited, with most women assuming execution roles in climate action rather than decision-making positions. (2) Millennial’s low-carbon life transition is accompanied by technological innovation and progress. However, this progress brings some new forms of resource waste, and reasonable policy-making is essential. (3) Personal economic interests and the satisfaction of their consumption needs will drive millennials to reduce carbon emissions in their daily lives, but it requires the guidance of reasonable policy-making and synergies among various stakeholders. This research will help policymakers better understand the current status and potential issues related to people’s low-carbon actions, enabling the formulation of more rational guiding policies. It can also help other stakeholders learn about millennials’ demands and take more effective collective action toward carbon reduction. Full article

Urgency urinary incontinence (UUI) refractory to medical treatment poses significant challenges despite advancements. This study evaluates the efficacy of intravesical botulinum toxin for UUI and identifies factors influencing treatment outcomes. Among 368 women receiving botulinum toxin injections, 74.5% achieved a complete discontinuation of pad usage. Predictors of efficacy included lower pre-treatment pad usage and the absence of prior sling placement. Patients often required repeat injections (60.3%), with younger age and satisfaction correlating with treatment repetition. The interval between injections averaged 18 months, influenced by logistical challenges and patient preferences. Despite concerns about diminishing efficacy, subjective perceptions did not align with objective findings. Limitations include retrospective analysis and heterogeneous clinical records. In conclusion, intravesical botulinum toxin is effective for UUI, with pre-treatment pad usage and sling placement history influencing outcomes and patient characteristics influencing treatment repetition. Full article

The quality of molten iron not only has a significant impact on the strength, toughness, smelting cost and service life of cast iron but also directly affects the satisfaction of users. The establishment of timely and accurate blast furnace molten iron quality prediction models is of great significance for the improvement of the production efficiency of blast furnace. In this paper, Si, S and P content in molten iron is taken as the important index to measure the quality of molten iron, and the 989 sets of production data from a No.1 blast furnace from August to October 2020 are selected as the experimental data source, predicting the quality of molten iron by the I-GWO-CNN-BiLSTM model. First of all, on the basis of the traditional data processing method, the missing data values are classified into correlation data, temporal data, periodic data and manual input data, and random forest, the Lagrangian interpolation method, the KNN algorithm and the SVD algorithm are used to complete them, so as to obtain a more practical data set. Secondly, CNN and BiLSTM models are integrated and I-GWO optimized hyperparameters are used to form the I-GWO-CNN-BiLSTM model, which is used to predict Si, S and P content in molten iron. Then, it is concluded that using the I-GWO-CNN-BiLSTM model to predict the molten iron quality can obtain high prediction accuracy, which can provide data support for the regulation of blast furnace parameters. Finally, the MCMC algorithm is used to analyze the influence of the input variables on the Si, S and P content in molten iron, which helps the steel staff control the quality of molten iron in a timely manner, which is conducive to the smooth running of blast furnace production. Full article