Falling is one of the most critical outcomes of loss of consciousness during triage in emergency department (ED). It is an important sign requires an immediate medical intervention. This paper presents a computer vision-based fall detection model in ED. In this study, we hypothesis that the proposed vision-based triage fall detection model provides accuracy equal to traditional triage system (TTS) conducted by the nursing team. Thus, to build the proposed model, we use MoveNet, a pose estimation model that can identify joints related to falls, consisting of 17 key points. To test the hypothesis, we conducted two experiments: In the deep learning (DL) model we used the complete feature consisting of 17 keypoints which was passed to the triage fall detection model and was built using Artificial Neural Network (ANN). In the second model we use dimensionality reduction Feature-Reduction for Fall model (FRF), Random Forest (RF) feature selection analysis to filter the key points triage fall classifier. We tested the performance of the two models using a dataset consisting of many images for real-world scenarios classified into two classes: Fall and Not fall. We split the dataset into 80% for training and 20% for validation. The models in these experiments were trained to obtain the results and compare them with the reference model. To test the effectiveness of the model, a t-test was performed to evaluate the null hypothesis for both experiments. The results show FRF outperforms DL model, and FRF has same accuracy of TTS.
Pakistan is a leading emerging market as per the recent classification of the International Monetary Fund (MF), and hedging is used as a considerable apparatus for minimizing a firm’s risk in this market. In these markets, investors are customarily unaware about the hedging activities in firms, due to the occupancy of asymmetric environment prevailing in firms. This research paper adds a new insight and vision to the existing literature in the field of behavioral finance by examining the impact of hedging on investors’ sentiments in the presence of asymmetric information. For organizing this research, 366 non-financial firms are taken up as the size sample; all these firms are registered in the Pakistan Stock Exchange. A two-step system of generalized method of moments (GMM) model is implemented for regulating the study. The findings of empirical evidence exhibit that there is a positive relationship between investors’ sentiments and hedging. Investors’ sentiments are negative in relationship with asymmetric information. Due to the moderate presence of asymmetric information, hedging is positively related to investors’ sentiments although this relation is non-significant.
Research that discusses the impact of implementing Green Human Resource Management and environmentally friendly behavior, especially in sustainable tourism, is limited. It becomes crucial to understand how implementing good green human resource management practices in tourism sector organizations. To achieve the objectives of this research, a qualitative approach was used where the data and information collected were obtained through direct observation and interviews with tourism informants. The findings show the importance of environmentally friendly behavior as the implementation of green human resource management is able to improve tourism management. The uniqueness of this research is developing a model of human resource readiness in implementing environmentally friendly behavior towards sustainable tourism. This resource readiness will be reflected in the GHRM model in supporting sustainable tourism. The results of this research offer a model of sustainable Green Tourism which includes antecedents, implementation and results achieved. These antecedents come from internal and external (environmental ethics and management commitment) managers which will result in good GHRM implementation. This model will be the basis for implementing sustainable tourism in human resource management practices based on literature reviews and also tourism management practices.
The research aims to examine East Nusa Tenggara (NTT) bank service digitalization innovations and examine several implications of bank service digitalization innovations. This research uses a qualitative approach with data collection techniques: in-depth interviews, documentation, and focused discussions. The key informants in this research were the board of commissioners, directors, division heads, and NTT bank employees. The findings of this research are, first, the existence of an existing/generic model in the operational, supporting, and monitoring fields of NTT banks. Second, there is an innovation model for digitizing services and efforts to popularize the digitization of NTT bank services to the government-private sector, including micro, small, and medium enterprises (MSMEs), religious institutions, educational institutions, students and students as well as the broader community to provide easy access to sources of financing for the community, Eliminate regional tax leakage, encourage the development of micro, small, and medium enterprises (MSMEs) and assisted village farmers/breeders, provide entrepreneurial opportunities for the community, namely as a digital agent for NTT bank, minimize fraudulent behavior (shirking) in credit distribution. Third, service digitalization innovation uses a contextual sociolinguistic approach because it incorporates local and global vocabulary such as Bpung Mobile, Bpung Farmer, Lopo Dia Bisa, and Bpinjam. Fourth, service digitalization innovation refers to OJK regulations regarding banking digital transformation contained in RP 21 and PBI number 23/26/2021. Fifth, conventional services (hybrid approach) still accompany the digitalization innovation model. Sixth, Bank NTT is in quadrant III, namely growth. Bank NTT continuously optimizes existing resources by taking advantage of opportunities to increase business growth and continues to mitigate threats into opportunities and strengths. The implications of the innovation in digitizing NTT bank services include updating standard operating procedures (SOP), changing corporate culture from Flobamora to Bintang, and accelerating the increase in human capital capacity. The implications of research on bank management refer to the innovation of procurement of new IT systems. Banks can increase their attention to service quality and maintain customer trust to maintain the quality of digital banks among customers. Moreover, with post-COVID-19 conditions that require people to make digital transactions. With the changes in the financial industry towards digitalization, it is necessary to strengthen risk management in financial service institutions. The implications of the research results for policymakers need to be considered in the transformation towards digital banking related to equitable internet access in Indonesia, cybersecurity, and employment. Recommendations for future research are the importance of studying the determinants of digital service innovation in bank services, such as transformational leadership style, good corporate governance, and organizational commitment.
The SMARTER model, an innovative educational framework, is designed for blended learning environments, seamlessly integrating both online and face-to-face instructional components. Employing a flipped classroom methodology, this model ensures an equitable division between online and traditional classroom interactions, aiming to cultivate a dynamic and collaborative learning atmosphere. This research focused on developing and rigorously evaluating the SMARTER model’s validity, practicality, and effectiveness. Adopting a research and development (R&D) approach informed by the methodologies of Borg, Gall, and Gall, this study utilized a mixed-methods strategy. This encompassed a robust validation process by experts in design, content, and media, alongside an empirical analysis of the model’s application in actual educational settings. The aim was to comprehensively assess its effectiveness and practicality. The findings from this study affirm the SMARTER model’s validity, practicality, and effectiveness in improving students’ information literacy skills. Comparative analysis between a control group, taught using a traditional expository approach, and an experimental group, educated under the SMARTER model, highlighted significant improvements in the latter group. This effectiveness underscores the model’s capacity not only to efficiently deliver content but also to actively engage students in a collaborative learning process. The results advocate for the model’s potential broader adoption and adaptation across similar educational contexts. They also establish a foundation for future research aimed at exploring the SMARTER model’s scalability and adaptability across diverse instructional environments.
The following paper assesses the relationship between electricity consumption, economic growth, environmental pollution, and Information and Communications Technology (ICT) development in Kazakhstan. Using the structural equation method, the study analyzes panel data gathered across various regions of Kazakhstan between 2014 and 2022. The data were sourced from official records of the Bureau of National Statistics of Kazakhstan and include all regions of Kazakhstan. The chosen timeframe includes the period from 2014, which marked a significant drop in oil prices that impacted the overall economic situation in the country, to 2022. The main hypotheses of the study relate to the impact of electricity consumption on economic growth, ICT, and environmental sustainability, as well as ICT’s role in economic development and environmental impact. The results show electricity consumption’s positive effect on economic growth and ICT development while also revealing an increase in pollutant emissions (emissions of liquid and gaseous pollutants) with economic growth and electricity consumption. The development of ICT in Kazakhstan has been revealed to not have a direct effect on reducing pollutant emissions into the environment, raising important questions about how technology can be leveraged to mitigate environmental impact, whether current technological advancements are sufficient to address environmental challenges, and what specific measures are needed to enhance the environmental benefits of ICT. There is a clear necessity to integrate sustainable practices and technologies to achieve balanced development. These results offer important insights into the relationships among electricity consumption, technology, economic development, and environmental issues. They underscore the complexity and multidimensionality of these interactions and suggest directions for future research, especially in the context of finding sustainable solutions for balanced development.
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