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People with visual impairments or blindness (PwVIB) are mostly excluded from tourism activities. Despite the rise of assistive technology (AT) solutions in Tourism, acceptance remains low because of the difficulty of providing the right functionality, effectiveness and usability. Arguably, it can be said that disability-oriented training can affect the latter two and, therefore, an AT solution’s acceptance. This paper aims to contribute to the theory development and conceptualization of technology acceptance of AT solutions in Tourism by studying, in the context of the Unified Theory of Acceptance and Use of Technology (UTAUT), the effects of training PwVIB on using AT solutions. This study presents the effects of training on the tourism behavior of PwVIB and provides valuable information to the stakeholders.

Questionnaire data collected from 128 PwVIB after evaluating an AT were subjected to exploratory and confirmatory factor analysis and structural equation modeling followed by post-evaluation interviews. The used application, called BlindMuseumTourer, enables high-precision autonomous indoor navigation for PwVIB in tourist places like museums and places of health care.

The results of this study indicate the partial satisfaction of the extended model validating the importance of performance expectancy and training (the new factor) in predicting the behavioral intention of PwVIB tourists toward using ATs during their tourist activities. This suggests that practitioners have to provide performant technological solutions accompanied by special training sessions for improved engagement and satisfaction.

This study contributes to the UTAUT theory in the context of Tourism for PwVIB by adding a new factor and replacing two moderator variables. To the best of the authors’ knowledge, no similar work is studying AT acceptance by PwVIB in the tourism literature. Furthermore, the validation process used a novel indoor navigation application, demonstrating its effectiveness in the Tactual Museum of Greece.

视障或失明人士（PwVIB）大多被排除在旅游活动之外。尽管辅助技术（AT）解决方案在旅游业中兴起, 但由于难以提供适当的功能、有效性和可用性, 接受度仍然很低。可以说, 以残疾为导向的培训会影响后两者, 从而影响对辅助技术解决方案的接受程度。本文旨在通过在技术接受和使用统一理论（UTAUT）的背景下, 研究培训 PwVIB 对使用 AT 解决方案的影响, 为旅游行业对 AT 解决方案的技术接受的理论发展和概念化做出贡献。本研究将介绍培训对 PwVIB 旅游行为的影响, 并为利益相关者提供有价值的信息。

对 128 名无身份者在评估了辅助设施后收集的问卷数据进行了探索性因素分析、确认性因素分析和结构方程模型分析, 然后进行了评估后访谈。所采用的应用程序名为 “BlindMuseumTourer”, 可在博物馆和医疗场所等旅游景点为 PwVIB 提供高精度的自主室内导航。

结果表明, 扩展模型的部分结果验证了性能预期和培训（新因素）在预测无障碍游客在旅游活动中使用自动视听设备的行为意向方面的重要性。这表明, 从业人员必须提供性能优越的技术解决方案, 并辅以专门的培训课程, 以提高参与度和满意度。

本研究通过增加一个新因素和替换两个调节变量, 为UTAUT 理论在无障碍游客旅游方面的应用做出了贡献。据我们所知, 在旅游文献中, 还没有类似的工作是研究 PwVIB 对 AT 的接受程度。此外, 在验证过程中还使用了一个新颖的室内导航应用程序, 并在希腊触觉博物馆展示了其有效性。

Las personas con discapacidad visual o ceguera (PwVIB) están excluidas en su mayoría de las actividades turísticas. A pesar del auge de las soluciones de tecnología de asistencia (TA) en el turismo, su aceptación sigue siendo baja debido a la dificultad de proporcionar la funcionalidad, eficacia y usabilidad adecuadas. Podría decirse que la formación orientada a la discapacidad puede afectar a las dos últimas y, por tanto, a la aceptación de una solución de TA. Este artículo pretende contribuir al desarrollo teórico y a la conceptualización de la aceptación de las soluciones de tecnología de apoyo en el turismo estudiando, en el contexto de la Teoría Unificada de la Aceptación y el Uso de la Tecnología (UTAUT), los efectos de la formación de las PwVIB en la utilización de las soluciones de tecnología de apoyo. El estudio presentará los efectos de la formación en el comportamiento turístico de las PwVIB y proporcionará información valiosa a las partes interesadas.

Los datos del cuestionario recogidos de 128 PwVIB tras la evaluación de una TA se sometieron a un Análisis Factorial Exploratorio y Confirmatorio y a un Modelado de Ecuaciones Estructurales, seguidos de entrevistas posteriores a la evaluación. La aplicación empleada, denominada BlindMuseumTourer, permite la navegación autónoma en interiores de alta precisión para PwVIB en lugares turísticos como museos y lugares de asistencia sanitaria.

Los resultados indican la satisfacción parcial del modelo ampliado validando la importancia de la expectativa de rendimiento y la formación en la predicción de la intención conductual de los turistas PwVIB por lo que sugieren a los profesionales que las sesiones especiales de formación son esenciales para el compromiso y la satisfacción de los usuarios.

Este estudio contribuye a la teoría UTAUT en el contexto del turismo para PwVIB añadiendo un nuevo factor y sustituyendo dos variables moderadoras. Hasta donde se sabe, no existe ningún trabajo similar que estudie la aceptación de la TA por parte de las PwVIB en la literatura sobre turismo. Además, en el proceso de validación se utilizó una novedosa aplicación de navegación en interiores que ha demostrado su eficacia en el Museo Táctico de Grecia.

Emissions have significant environmental impacts. Hence, minimizing emissions is essential. This study aims to use a hybrid neural network model to predict carbon monoxide (CO) and nitrogen oxide (NOx) emissions from gas turbines (GTs) to enhance emission prediction for GTs in predictive emissions monitoring systems (PEMS).

The hybrid model architecture combines convolutional neural networks (CNN) and bidirectional long-short-term memory (Bi-LSTM) networks called CNN-BiLSTM with modified extrinsic attention regression. Over five years, data from a GT power plant was uploaded to Google Colab, split into training and testing sets (80:20), and evaluated using test matrices. The model’s performance was benchmarked against state-of-the-art emissions prediction methodologies.

The model showed promising results for GT CO and NOx emissions. CO predictions had a slight underestimation bias of −0.01, with root mean-squared error (RMSE) of 0.064, mean absolute error (MAE) of 0.04 and R² of 0.82. NOx predictions had an RMSE of 0.051, MAE of 0.036, R² of 0.887 and a slight overestimation bias of +0.01.

While the model demonstrates relative accuracy in CO emission predictions, there is potential for further improvement in future research.

Implementing the model in real-time PEMS and establishing a continuous feedback loop will ensure accuracy in real-world applications, enhance GT functioning and reduce emissions, fuel consumption and running costs.

Accurate GT emissions predictions support stricter emission standards, promote sustainable development goals and ensure a healthier societal environment.

This paper presents a novel approach that integrates CNN and Bi-LSTM networks. It considers both spatial and temporal data to mitigate previous prediction shortcomings.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether media richness and social interaction as environmental feature antecedents to nurses’ learning engagement (LE) can affect their continuance intention of massive open online courses (MOOCs) and task performance.

Sample data for this study were collected from nurses at five university-/medical university-affiliated hospitals in Taiwan. A total of 500 questionnaires were distributed, and 303 (60.6%) usable questionnaires were analyzed using structural equation modeling in this study.

This study proved that nurses’ perceived media richness and social interaction in MOOCs positively influenced their behavioral LE and psychological LE elicited by MOOCs, which jointly caused their continuance intention of MOOCs and, in turn, enhance their task performance. The results support all proposed hypotheses and the research model, respectively, explains 84.3% and 63.7% of the variance in nurses’ continuance intention of MOOCs and task performance.

This study uses the S-O-R model as a theoretical base to frame nurses’ continuance intention of MOOCs and task performance as a series of the internal process, which is affected by environmental stimuli (i.e. media richness and social interaction) and organismic states. Noteworthily, while the S-O-R model has been extensively used in prior literature, little research uses this paradigm to expound nurses’ continuance intention of MOOCs in the work settings. Besides, there is a dearth of evidence on the antecedents of nurses’ task performance in the context of MOOCs. Hence, this study’s empirical evidence contributes significantly to the existing literature on bridging the gap of limited evaluation for the research on the impact of nurses’ MOOCs learning on their task performance in the work settings, which is very scarce in the S-O-R view.

Recognizing construction workers' activities is critical for on-site performance and safety management. Thus, this study presents the potential of automatically recognizing construction workers' actions from activations of the erector spinae muscles.

A lab study was conducted wherein the participants (n = 10) performed rebar task, which involved placing and tying subtasks, with and without a wearable robot (exoskeleton). Trunk muscle activations for both conditions were trained with nine well-established supervised machine learning algorithms. Hold-out validation was carried out, and the performance of the models was evaluated using accuracy, precision, recall and F1 score.

Results indicate that classification models performed well for both experimental conditions with support vector machine, achieving the highest accuracy of 83.8% for the “exoskeleton” condition and 74.1% for the “without exoskeleton” condition.

The study paves the way for the development of smart wearable robotic technology which can augment itself based on the tasks performed by the construction workers.

This study contributes to the research on construction workers' action recognition using trunk muscle activity. Most of the human actions are largely performed with hands, and the advancements in ergonomic research have provided evidence for relationship between trunk muscles and the movements of hands. This relationship has not been explored for action recognition of construction workers, which is a gap in literature that this study attempts to address.

The digital warehouse management system is an emergence that forms a critical part of the transformation of economic structure in Industry 4.0. In the present business scenario, the warehouse management system encounters a messy layout, poor damage control, unsatisfactory order management, lack of visibility and lack of technological interventions. Digital twin (DT) based warehouse system shows the ontology and knowledge graphs for competitive advantage by consolidating and transferring goods directly from an inbound supplier to an outbound customer on short notice and with no or limited storage. There remains a lack of clarity on how the DT can be implemented successfully in warehouse management.

The current literature remains largely unstructured and scattered due to a lack of a systematic approach to integrating the research implications and analysis. This paper probes the conceptualization of the DT with the help of theoretical analysis using the systematic literature analysis method.

The study explores essential concepts such as interoperability and integrability in implementing DT. Further, it analyzes the role of a supply chain control tower (SCCT) in modern supply chain management. A research framework is proposed for practitioners and academicians by incorporating the opportunities and challenges associated with DT implementation. The research findings are mainly threefold: Conceptualization of DT, Featuring SCCT and Exploration of cross-computer platform interfaces, scalability and maintenance strategies.

This study is among the first to analyze and review DT applications in warehouse management. Moreover, the study proposes a theoretical toolbox for the practitioners to successfully implement the DT in warehouse DT-based warehouse management system: A theoretical toolbox for future research and applications.

Devices for step estimation are body-worn devices used to compute steps taken and/or distance covered by the user. Even though textiles or clothing are foremost to come to mind in terms of articles meant to be worn, their prominence among devices and systems meant for cadence is overshadowed by electronic products such as accelerometers, wristbands and smart phones. Athletes and sports enthusiasts using knee sleeves should be able to track their performances and monitor workout progress without the need to carry other devices with no direct sport utility, such as wristbands and wearable accelerometers. The purpose of this study thus is to contribute to the broad area of wearable devices for cadence application by developing a cheap but effective and efficient stride measurement system based on a knee sleeve.

A textile strain sensor is designed by weft knitting silver-plated nylon yarn together with nylon DTY and covered elastic yarn using a 1 × 1 rib structure. The area occupied by the silver-plated yarn within the structure served as the strain sensor. It worked such that, upon being subjected to stress, the electrical resistance of the sensor increases and in turn, is restored when the stress is removed. The strip with the sensor is knitted separately and subsequently sewn to the knee sleeve. The knee sleeve is then connected to a custom-made signal acquisition and processing system. A volunteer was employed for a wearer trial.

Experimental results establish that the number of strides taken by the wearer can easily be correlated to the knee flexion and extension cycles of the wearer. The number of peaks computed by the signal acquisition and processing system is therefore counted to represent stride per minute. Therefore, the sensor is able to effectively count the number of strides taken by the user per minute. The coefficient of variation of over-ground test results yielded 0.03%, and stair climbing also obtained 0.14%, an indication of very high sensor repeatability.

The study was conducted using limited number of volunteers for the wearer trials.

By embedding textile piezoresistive sensors in some specific garments and or accessories, physical activity such as gait and its related data can be effectively measured.

To the best of our knowledge, this is the first application of piezoresistive sensing in the knee sleeve for stride estimation. Also, this study establishes that it is possible to attach (sew) already-knit textile strain sensors to apparel to effectuate smart functionality.

This study aims to assess the use of the Internet of Things (IoT) in retail stores to improve supply chain visibility and integration.

This study employed a qualitative methodology with data collected using semi-structured interviews from a sample selected using purposive sampling. The population consists of 48 employees, of which 6 were selected for the sample as they worked directly with IoT and supply chain issues. Participants were from a SPAR franchise store (Samenwerken Profiteren Allen Regalmatig).

Thematic analysis was used to analyse the transcribed data from the interviews. The themes identified include supply chain visibility, supply chain integration and IoT. The findings indicate that the main IoT used is an organisational-wide system, the SIGMA (SPAR Integrated Goods Management Application) system. Other technologies that aid supply chain visibility and integration are geotags, the internet, WhatsApp social media applications, emails and scanners.

From the findings, this study recommends that IoT systems should be frequently updated to reflect current trends and that IoT systems should enable the integration of small and medium Enterprises (SMEs) suppliers.

The Fourth Industrial Revolution has ushered in new technologies that revolutionise business operations. Among these technologies is the IoT, which has ushered in a new connectivity area. However, there is little research on the use of IoT for supply chain visibility and integration in the South African retail sector. It provides sector-specific insights and recommendations for retailers, which might not be covered in general supply chain management literature.

The current work investigates an unsteady squeezed flow of hybrid-nanofluid between two parallel plates in occurrence with a uniform transverse magnetic field. Water is used as base fluid mixed with Graphene Oxide (GO) and Copper (Cu) nanoparticles. The flow considered here is under slip boundary conditions.

The governing PDEs are transmuted into ODEs by applying an appropriate similarity transformation and then solved numerically using the 4th order R-K method with shooting technique. Graphical illustrations for velocity, temperature, entropy generation (NG), Bejan number (Be), streamline etc. are presented and discussed in detail from the physical point of view. The nature of the Nusselt number is also studied numerically through contour plots for different flow parameters.

There is no funding obtained for the research work.

This kind of study may be used in various fields including polymer processing, lubrication apparatus, compression including hydrodynamical machines compression, food processing etc.

It is observed that very little investigation has yet been made about the movement of hybrid nanofluid between two analogous plates.

COVID entered the world in 2019 as a pandemic and the intensity of this health crisis is only increasing in several regions. Therefore, it is critical to study and detect the public's frame of mind, government and economists' perception regarding the COVID crisis, as well as the primary worries that the public has expressed, and how this evolves over time. Responsive measures towards COVID-19 from the Indian economy have been explored as a key objective. Moreover, efforts have been made to explore recovery in India through economists and policymakers. Data have been explored through online interviews of key economists which were published in leading newspapers and covered through media channels such as NDTV, CNBC, etc. Moreover, various newspapers and reports were explored to understand government initiatives to address COVID-19 in India. The study's findings show how essential economic recovery from the second wave is in India, and how it may be achieved by strong fiscal and monetary policies, as well as specific attention to impoverished households, small and micro-businesses and increased employment. The short-term focus of the developing economic strategy must be on giving crisis relief to the most unprotected segments of society since long-term system stimulation is impossible.

Construction is a risky industry. Therefore, organizations are seeking ways towards improving their safety performance. Among these, the integration of technology into health and safety leads to enhanced safety performance. Considering the benefits observed in using technology in safety, this study aims to explore digital technologies' use and potential benefits in construction health and safety.

An extensive bibliometrics analysis was conducted to reveal which technologies are at the forefront of others and how these technologies are used in safety operations. The study used two different databases, Web of Science (WoS) and Scopus, to scan the literature in a systemic way.

The systemic analysis of several studies showed that the digital technologies use in construction are still a niche theme and need more assessment. The study provided that sensors and wireless technology are of utmost importance in terms of construction safety. Moreover, the study revealed that artificial intelligence, machine learning, building information modeling (BIM), sensors and wireless technologies are trending technologies compared to unmanned aerial vehicles, serious games and the Internet of things. On the other hand, the study provided that the technologies are even more effective with integrated use like in the case of BIM and sensors or unmanned aerial vehicles. It was observed that the use of these technologies varies with respect to studies conducted in different countries. The study further revealed that the studies conducted on this topic are mostly published in some selected journals and international collaboration efforts in terms of researching the topic have been observed.

This study provides an extensive analysis of WoS and Scopus databases and an in-depth review of the use of digital technologies in construction safety. The review consists of the most recent studies showing the benefits of using such technologies and showing the usage on a systemic level from which both scientists and practitioners can benefit to devise new strategies in technology usage.